Ventana Research Analyst Perspectives

The data platforms market has traditionally been divided between products specifically designed to support operational or analytic workloads, with other market segments having emerged in recent years for data platforms targeted specifically at data science and machine learning (ML), as well as real-time analytics. More recently, we have seen vendor strategies evolving to provide a more consolidated approach, with data platforms designed to address a combination of analytics and data science, as well as hybrid operational and analytic processing. Snowflake, which has been hugely successful in recent years with its cloud-based analytic data platform, is a prime example. The company has expanded its purview to address data engineering and data science, as well as transactional data. Additionally, it now provides users with the ability to access and process data in on-premises environments as part of its strategy to address an increasing range of use cases.

The recent publication of our Value Index research highlights the impact of intelligent applications on the operational data platforms sector. While we continue to believe that, for most use cases, there is a clear, functional requirement for either analytic or operational data platforms, recent growth in the development of intelligent applications infused with the results of analytic processes, such as personalization and artificial intelligence (AI)-driven recommendations, has increasing influence over requirements for operational data platforms to support real-time analytic functionality. Operational data platform vendors, including MongoDB, are responding to these evolving requirements with new functionality to support the development and deployment of intelligent applications. 

I have previously written about the importance of data democratization as a key element of a data-driven agenda. Removing barriers that prevent or delay users from gaining access to data enables it to be treated as a product that is generated and consumed, either internally by employees or externally by partners and customers. This is particularly important for organizations adopting the data mesh approach to data ownership, access and governance. Data mesh is an organizational and cultural approach to data, rather than a technology platform. Nevertheless, multiple vendors are increasingly focused on providing products that facilitate adoption of data mesh and promote data democratization. Amazon Web Services is one such vendor, thanks to the recent launch of Amazon DataZone, one of the figurehead analytics and data announcements made during the company’s recent re:Invent customer event.

I recently wrote about the potential use cases for distributed SQL databases as well as techniques being employed by vendors to accelerate adoption. Distributed SQL is a term that is used by several vendors to describe operational data platform products that combine the benefits of the relational database model and native support for distributed cloud architecture, including resilience that spans multiple data centers and/or cloud regions. I noted that compatibility with existing database tools and skills was a key factor for these vendors as they lower barriers to developer adoption. A prime example is Cockroach Labs, which highlighted the importance of compatibility and developer efficiency with the recent launch of CockroachDB 22.2.

Data observability was a hot topic in 2022 and looks likely to be a continued area of focus for innovation in 2023 and beyond. As I have previously described, data observability software is designed to automate the monitoring of data platforms and data pipelines, as well as the detection and remediation of data quality and data reliability issues. There has been a Cambrian explosion of data observability software vendors in recent years, and while they have fundamental capabilities in common, there is also room for differentiation. One such vendor is Soda Data, which offers an open-source platform for self-service data observability that is focused on facilitating collaboration between business decision-makers and data teams responsible for generating and managing data to improve trust in data.

I have written about the increased demand for data-intensive operational applications infused with the results of analytic processes, such as personalization and artificial intelligence-driven recommendations. I previously described the use of hybrid data processing to enable analytics on application data within operational data platforms. As is often the case in the data platforms sector, however, there is more than one way to peel an orange. Recent years have also seen the emergence of several analytic data platforms that deliver real-time analytic processing suitable for data-intensive operational applications.

Despite the emphasis on organizations being more data-driven and making an increasing proportion of business decisions based on data and analytics, it remains the case that some of the most fundamental questions about an organization are difficult to answer using data and analytics. Ostensibly simple questions such as, “how many customers does the organization have?” can be fiendishly difficult to answer, especially for organizations with multiple business entities, regions, departments and applications. Increasing volumes and sources of data can hinder, rather than help. Only 1 in 5 participants (20%) in Ventana Research’s Analytics and Data Benchmark research are very confident in their organization’s ability to analyze the overall quantity of data. This is a perennial issue that data and application integration vendors, such as SnapLogic, are aiming to address – increasingly through automation and products for business users as well as data management professionals.

I am happy to share insights from our latest Ventana Research Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements. The 2023 Analytic Data Platforms Value Index is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect real-world criteria incorporated in a request for proposal to data platform vendors supporting the spectrum of analytic use-cases. Using this methodology, we evaluated vendor submissions in seven categories: five relevant to the Product Experience: Adaptability, Capability, Manageability, Reliability and Usability, and two related to the Customer Experience: Total Cost of Ownership/Return on Investment and Validation. This research-based index evaluates the full business and information technology value of analytic data platforms offerings. I encourage you to learn more about our Value Index and its effectiveness as a vendor selection and request for information/requestion for proposal tool.

Ventana Research recently published the 2023 Analytic Data Platforms Value Index. As organizations strive to be more data-driven, increasing reliance on data as a fundamental factor in business decision-making, the importance of the analytic data platform has never been greater. In this post, I’ll share some of my observations about how the analytic data platforms market is evolving.

I am happy to share insights from our latest Ventana Research Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements. The 2023 Operational Data Platforms Value Index is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect real-world criteria incorporated in a request for proposal to data platform vendors supporting the spectrum of operational use cases. Using this methodology, we evaluated vendor submissions in seven categories: five relevant to the Product Experience: Adaptability, Capability, Manageability, Reliability and Usability, and two related to the Customer Experience: Total Cost of Ownership/Return on Investment and Validation.

Ventana Research recently announced its 2023 Market Agenda for Data, continuing the guidance we have offered for two decades to help organizations derive optimal value and improve business outcomes.

Ventana Research recently published the 2023 Operational Data Platforms Value Index. The importance of the operational data platform has never been greater as organizations strive to be more data-driven, incorporating intelligence into operational applications via personalization and recommendations for workers, partners and customers. In this post, I’ll share some of my observations on how the operational data platforms market is evolving.

I am happy to share insights from our latest Ventana Research Value Index, which assesses how well vendors’ offerings meet buyers’ requirements. The 2023 Data Platforms Value Index is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect real-world criteria incorporated in a request for proposal to data platform vendors that support the spectrum of operational and analytic use cases. Using this methodology, we evaluated vendor submissions in seven categories: five relevant to the Product Experience: Adaptability, Capability, Manageability, Reliability and Usability, and two related to the Customer Experience: Total Cost of Ownership/Return on Investment and Validation.

I’m proud to share Ventana Research’s 2023 Market Agenda for Digital Technology. Our focus in this agenda is to deliver expertise to help organizations prioritize technology investments that improve customer, partner and workforce experiences while also increasing organizational effectiveness and agility.

Vertical strategies for enterprise resource planning systems are not new. They emerged more than two decades ago as vendors looked for ways to reduce costs and shorten time-to-value in a software category that was notorious for high costs and extended timelines. A vertical-plus strategy – the plus means it’s a platform, not just an application – takes advantage of recently available technology to extend the ease of implementation and maintenance of the system by having deeper integration with complementary applications, available low-code/no-code customization capabilities and a data pantry that enables the amalgamation of data from multiple sources for situational awareness and decision support. Moreover, the ongoing shift from on-premises to cloud-based ERP systems, especially those designed to address specific types of businesses, will accelerate over the next five years as more configurable and customizable systems designed for specific business verticals become available. A cloud-based platform facilitates the creation of a digital ecosystem that can enable a software vendor’s users to enhance customer experiences.

Data observability is a hot topic and trend. I have written about the importance of data observability for ensuring healthy data pipelines, and have covered multiple vendors with data observability capabilities, offered both as standalone and part of a larger data engineering system. Data observability software provides an environment that takes advantage of machine learning and DataOps to automate the monitoring of data quality and reliability. The term has been adopted by multiple vendors across the industry, and while they all have key functionality in common – including collecting and measuring metrics related to data quality and data lineage – there is also room for differentiation. A prime example is Acceldata, which takes a position that data observability requires monitoring not only data and data pipelines but also the underlying data processing compute infrastructure as well as data access and usage.

Having recently completed the 2023 Data Platforms Value Index, I want to share some of my observations about how the market is evolving. Although this is our inaugural assessment of the market for data platforms, the sector is mature and products from many of the vendors we assess can be used to effectively support operational and analytic use cases.

The shift from on-premises server infrastructure to cloud-based and software-as-a-service (SaaS) models has had a profound impact on the data and analytics architecture of many organizations in recent years. More than one-half of participants (59%) in Ventana Research’s Analytics and Data Benchmark research are deploying data and analytics workloads in the cloud, and a further 30% plan to do so. Customer demand for cloud-based consumption models has also had a significant impact on the products and services that are available from data and analytics vendors. Data platform providers, both operational and analytic, have had to adapt to changing customer demand. The initial response — making existing products available for deployment on cloud infrastructure — only scratched the surface in terms of responding to emerging expectations. We now see the next generation of products, designed specifically to deliver innovation by taking advantage of cloud-native architecture, being brought to market both by emerging startups, and established vendors, including InterSystems.

There is always space for innovation in the data platforms sector, and new vendors continue to emerge at regular intervals with new approaches designed to serve specialist data storage and processing requirements. Factors including performance, reliability, security and scalability provide a focal point for new vendors to differentiate from established vendors, especially for the most demanding operational or analytic data platform requirements. It is never easy, however, for developers of new data platform products to gain significant market traction, given the dominance of the established relational database vendors and cloud providers. Targeting requirements that are not well-served by general purpose data platforms can help new vendors get a toe in the door of customer accounts. The challenge to gaining further market traction is for new vendors to avoid having products become pigeon-holed as only being suitable for a niche set of requirements. This is precisely the problem facing the various distributed SQL database providers.

In previous perspectives in this series, I’ve discussed some of the realities of cloud computing including costs, hybrid and multi-cloud configurations and business continuity. This perspective examines the realities of security and regulatory concerns associated with cloud computing. These issues are often cited by our research participants as reasons they are not embracing the cloud. To be fair, the majority of our research participants are embracing the cloud. However, among those that have not yet made the transition to the cloud, security and regulatory concerns are among the most common issues cited across the various studies we have conducted.

Earlier this year, I wrote about the increasing importance of data observability, an emerging product category that takes advantage of machine learning (ML) and Data Operations (DataOps) to automate the monitoring of data used for analytics projects to ensure its quality and lineage. Monitoring the quality and lineage of data is nothing new. Manual tools exist to ensure that it is complete, valid and consistent, as well as relevant and free from duplication. Data observability vendors, including Monte Carlo Data, have emerged in recent years with the goal of increasing the productivity of data teams and improving organizations’ trust in data using automation and artificial intelligence and machine learning (AI/ML).

In my previous perspectives on cloud computing, I addressed some of the realities of cloud costs as well as hybrid and multi-cloud architectures. In the midst of the pandemic, my colleague, Mark Smith, authored a series of perspectives on considerations for business continuity in general, beginning with this look at some of the investments organizations must make to mitigate the risk of business disruptions. In this perspective, I’d like to address some of the realities of business continuity and cloud computing and how they impact the digital technologies of an organization. The cloud can be both advantageous and disadvantageous when it comes to providing business continuity.

I have written recently about the similarities and differences between data mesh and data fabric. The two are potentially complementary. Data mesh is an organizational and cultural approach to data ownership, access and governance. Data fabric is a technical approach to automating data management and data governance in a distributed architecture. There are various definitions of data fabric, but key elements include a data catalog for metadata-driven data governance and self-service, agile data integration.

I have written before about the continued use of specialist operational and analytic data platforms. Most database products can be used for operational or analytic workloads, and the number of use cases for hybrid data processing is growing. However, a general-purpose database is unlikely to meet the most demanding operational or analytic data platform requirements. Factors including performance, reliability, security and scalability necessitate the use of specialist data platforms. I assert that through 2026, and despite increased demand for hybrid operational and analytic processing, more than three-quarters of data platform use cases will have functional requirements that encourage the use of specialized analytic or operational data platforms. It is for that reason that specialist database providers, including Ocient, continue to emerge with new and innovative approaches targeted at specific data-processing requirements.

Earlier this year I described the growing use-cases for hybrid data processing. Although it is anticipated that the majority of database workloads will continue to be served by specialist data platforms targeting operational and analytic workloads respectively, there is increased demand for intelligent operational applications infused with the results of analytic processes, such as personalization and artificial intelligence-driven recommendations. There are multiple data platform approaches to delivering real-time data processing and analytics, including the use of streaming data and event processing and specialist, real-time analytic data platforms. We also see operational data platform providers, such as Aerospike, adding analytic processing capabilities to support these application requirements via hybrid operational and analytic processing.

I have recently written about the organizational and cultural aspects of being data-driven, and the potential advantages data-driven organizations stand to gain by responding faster to worker and customer demands for more innovative, data-rich applications and personalized experiences. I have also explained that data-driven processes require more agile, continuous data processing, with an increased focus on extract, load and transform processes — as well as change data capture and automation and orchestration — as part of a DataOps approach to data management. Safeguarding the health of data pipelines is fundamental to ensuring data is integrated and processed in the sequence required to generate business intelligence. The significance of these data pipelines to delivering data-driven business strategies has led to the emergence of vendors, such as Astronomer, focused on enabling organizations to orchestrate data engineering pipelines and workflows.

In my first perspective on cloud computing realities, I covered some of the cost considerations associated with cloud computing and how the cloud costing model may be different enough from on-premises models that some organizations are taken by surprise. In this perspective. I’d like to focus on realities of hybrid and multi-cloud deployments.

I recently wrote about the need for organizations to take a holistic approach to the management and governance of data in motion alongside data at rest. As adoption of streaming data and event processing increases, it is no longer sufficient for streaming data projects to exist in isolation. Data needs to be managed and governed regardless of whether it is processed in batch or as a stream of events. This requirement has resulted in established data management vendors increasing their focus on streaming data and event processing through product development as well as acquisitions. It has also resulted in streaming and event specialists, such as Confluent, adding centralized management and governance capabilities to their existing offerings as they seek to establish or reinforce the strategic importance of streaming data as part of a modern approach to data management.

The migration to cloud is obvious. Organizations are adopting cloud computing for all variety of applications and use cases. Managed cloud services, commonly referred to as software as a service (SaaS), offer many benefits to organizations including significantly reduced labor costs for system administration and maintenance, as many of these costs are shifted to the software vendor. SaaS also provides organizations with faster time to value as they adopt new technologies by eliminating the need to acquire and configure hardware, and it also eliminates the need to install software. In fact, we assert that by 2025, nine in 10 organizations will be using multiple cloud applications in order to minimize the costs of administration and maintenance. Yet, there are some challenges associated with cloud computing I’d like to address in a series of Analyst Perspectives:

I have written recently about increased demand for data-intensive applications infused with the results of analytic processes, such as personalization and artificial intelligence (AI)-driven recommendations. Almost one-quarter of respondents (22%) to Ventana Research’s Analytics and Data Benchmark Research are currently analyzing data in real time, with an additional 10% analyzing data every hour. There are multiple data platform approaches to delivering real-time data processing and analytics and more agile data pipelines. These include the use of streaming and event data processing, as well as the use of hybrid data processing to enable analytics to be performed on application data within operational data platforms. Another approach, favored by a group of emerging vendors such as Rockset, is to develop these data-intensive applications on a specialist, real-time analytic data platform specifically designed to meet the performance and agility requirements of data-intensive applications.

I have recently written about the importance of healthy data pipelines to ensure data is integrated and processed in the sequence required to generate business intelligence, and the need for data pipelines to be agile in the context of real-time data processing requirements. Data engineers, who are responsible for monitoring, managing and maintaining data pipelines, are under increasing pressure to deliver high-performance and flexible data integration and processing pipelines that are capable of handling the rising volume and frequency of data. Automation is a potential solution to this challenge, and several vendors, such as Ascend.io, have emerged in recent years to reduce the manual effort involved in data engineering.

I recently wrote about the growing range of use cases for which NoSQL databases can be considered, given increased breadth and depth of functionality available from providers of the various non-relational data platforms. As I noted, one category of NoSQL databases — graph databases — are inherently suitable for use cases that rely on relationships, such as social media, fraud detection and recommendation engines, since the graph data model represents the entities and values and also the relationships between them. The native representation of relationships can also be significant in surfacing “features” for use in machine learning modeling. There has been a concerted effort in recent years by graph database providers, including TigerGraph, to encourage and facilitate the use of graph databases by data scientists to support the development, testing and deployment of machine learning models.

I previously described the concept of hydroanalytic data platforms, which combine the structured data processing and analytics acceleration capabilities associated with data warehousing with the low-cost and multi-structured data storage advantages of the data lake. One of the key enablers of this approach is interactive SQL query engine functionality, which facilitates the use of existing business intelligence (BI) and data science tools to analyze data in data lakes. Interactive SQL query engines have been in use for several years — many of the capabilities were initially used to accelerate analytics on Hadoop — but have evolved along with data lake initiatives to enable analysis of data in cloud object storage. The open source Presto project is one of the most prominent interactive SQL query engines and has been adopted by some of the largest digital-native organizations. Presto managed-services provider Ahana is on a mission to bring the advantages of Presto to the masses.

As I recently described, it is anticipated that the majority of database workloads will continue to be served by specialist data platforms targeting operational and analytic workloads, albeit with growing demand for hybrid data processing use-cases and functionality. Specialist operational and analytic data platforms have historically been the since preferred option, but there have always been general-purpose databases that could be used for both analytic and operational workloads, with tuning and extensions to meet the specific requirements of each.

I recently described the use cases driving interest in hybrid data processing capabilities that enable analysis of data in an operational data platform without impacting operational application performance or requiring data to be extracted to an external analytic data platform. Hybrid data processing functionality is becoming increasingly attractive to aid the development of intelligent applications infused with personalization and artificial intelligence-driven recommendations. These applications can be used to improve customer service; engagement, detect and prevent fraud; and increase operational efficiency. Several database providers now offer hybrid data processing capabilities to support these application requirements. One of the vendors addressing this opportunity is SingleStore.

The server is a key component of enterprise computing, providing the functional compute resources required to support software applications. Historically, the server was so fundamentally important that it – along with the processor, or processor core – was also a definitional unit by which software was measured, priced and sold. That changed with the advent of cloud-based service delivery and consumption models.

Over a decade ago, I coined the term NewSQL to describe the new breed of horizontally scalable, relational database products. The term was adopted by a variety of vendors that sought to combine the transactional consistency of the relational database model with elastic, cloud-native scalability. Many of the early NewSQL vendors struggled to gain traction, however, and were either acquired or ceased operations before they could make an impact in the crowded operational data platforms market. Nonetheless, the potential benefits of data platforms that span both on-premises and cloud resources remain. As I recently noted, many of the new operational database vendors have now adopted the term “distributed SQL” to describe their offerings. In addition to new terminology, a key trend that separates distributed SQL vendors from the NewSQL providers that preceded them is a greater focus on developers, laying the foundation for the next generation of applications that will depend on horizontally scalable, relational-database functionality. Yugabyte is a case in point.

I’m proud to share Ventana Research’s 2022 Market Agenda for Digital Technology. Our focus in this agenda is to deliver expertise to help organizations prioritize technology investments that increase workforce effectiveness and organizational agility, ensuring ongoing operations during any type of disruption.

The need for data-driven decision-making requires organizations to transform not only the approach to business intelligence and data science but also accelerate the development of new operational applications that support greater business agility, enable cloud- and mobile-based consumption, and deliver more interactive and personalized experiences. To stay competitive, organizations need to prioritize the development of new, data-driven applications. As a result, many have been encouraged to invest in new data platforms designed to support agile development and cloud-based delivery. This is one of the factors driving the growth of MongoDB, and continues to drive the evolution of its document database into what is now described as a cloud-based application data platform.

Data lakes have enormous potential as a source of business intelligence. However, many early adopters of data lakes have found that simply storing large amounts of data in a data lake environment is not enough to generate business intelligence from that data. Similarly, lakes and reservoirs have enormous potential as sources of energy. However, simply storing large amounts of water in a lake is not enough to generate energy from that water. A hydroelectric power station is required to harness and unleash the power-generating potential of a lake or reservoir, utilizing a combination of turbines, generators and transformers to convert the energy of the flowing water into electricity. A hydroanalytic data platform, the data equivalent of a hydroelectric power station, is required to harness and unleash the intelligence-generating potential of a data lake.

Breaking into the database market as a new vendor is easier said than done given the dominance of the sector by established database and data management giants, as well as the cloud computing providers. We recently described the emergence of a new breed of distributed SQL database providers with products designed to address hybrid and multi-cloud data processing. These databases are architecturally and functionally differentiated from both the traditional relational incumbents (in terms of global scalability) and the NoSQL providers (in terms of the relational model and transactional consistency). Having differentiated functionality is the bare minimum a new database vendor needs to make itself known in a such a crowded market, however.

Enterprises looking to adopt cloud-based data processing and analytics face a disorienting array of data storage, data processing, data management and analytics offerings. Departmental autonomy, shadow IT, mergers and acquisitions, and strategic choices mean that most enterprises now have the need to manage data across multiple locations, while each of the major cloud providers and data and analytics vendors has a portfolio of offerings that may or may not be available in any given location. As such, the ability to manage and process data across multiple clouds and data centers is a growing concern for large and small enterprises alike. Almost one-half (49%) of respondents to Ventana Research’s Analytics and Data Benchmark Research study are using cloud computing for analytics and data, of which 42% are currently using more than one cloud provider.

The work environment today demands that your organization advances the efficiency to execute business processes for continuous operations to have a positive impact on business performance. The capability to be responsive to any range of minor to disruptive business events is required to support business continuity and level of organizational readiness to meet the needs of digital business. Ventana Research asserts that in 2025, one-quarter of organizations will remain digitally ineffective in achieving the business priorities for customer-, product- and people-related processes. It is essential to eliminate bottlenecks and become an organization that places action and decision-making at is center to optimize the execution of business processes.

I’m proud to share Ventana Research’s 2021 market agenda for digital technology. Our focus in this agenda is to deliver expertise to help organizations prioritize technology investments that increase workforce effectiveness and organizational agility, ensuring ongoing operation during any type of disruption.

We are happy to offer some insights on Qlik drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements. Earlier this year we published the Ventana Research Value Index: Analytics and Business Intelligence 2019, the distillation of a year of market and product research efforts. We then developed three additional Value Indexes on Analytics and BI focusing on mobile, embedded and collaborative capabilities. Because each is a critical aspect of modern business intelligence, we developed specific criteria for each in order to provide an in-depth look at features geared specifically to mobile, embedded and collaborative use.

We are happy to offer some insights on Microsoft drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements. Earlier this year we published the Ventana Research Value Index: Analytics and Business Intelligence 2019, the distillation of a year of market and product research efforts. We then developed three additional Value Indexes on Analytics and BI focusing on mobile, embedded and collaborative capabilities. Because each is a critical aspect of modern business intelligence, we developed specific criteria for each in order to provide an in-depth look at features geared specifically to mobile, embedded and collaborative use.

We are happy to offer some insights on Looker drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements. Earlier this year we published the Ventana Research Value Index: Analytics and Business Intelligence 2019, the distillation of a year of market and product research efforts. We then developed three additional Value Indexes on Analytics and BI focusing on mobile, embedded and collaborative capabilities. Because each is a critical aspect of modern business intelligence, we developed specific criteria for each in order to provide an in-depth look at features geared specifically to mobile, embedded and collaborative use.

We are happy to offer some insights on Tableau drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements. Earlier this year we published the Ventana Research Value Index: Analytics and Business Intelligence 2019, the distillation of a year of market and product research efforts by Ventana Research. We then developed three additional Value Indexes on Analytics and BI focusing on mobile, embedded and collaborative capabilities. Because each is a critical aspect of modern business intelligence, we developed specific criteria for each in order to provide an in-depth look at features geared specifically to mobile, embedded and collaborative use.

We are happy to offer some insights on Oracle drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements. Earlier this year we published the Ventana Research Value Index: Analytics and Business Intelligence 2019, the distillation of a year of market and product research efforts. We then developed three additional Value Indexes on Analytics and BI focusing on mobile, embedded and collaborative capabilities. Because each is a critical aspect of modern business intelligence, we developed specific criteria for each in order to provide an in-depth look at features geared specifically to mobile, embedded and collaborative use.

We are happy to offer some insights on Salesforce drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements. Earlier this year we published the Ventana Research Value Index: Analytics and Business Intelligence 2019, the distillation of a year of market and product research efforts by Ventana Research. We then developed three additional Value Indexes on Analytics and BI focusing on mobile, embedded and collaborative capabilities. Because each is a critical aspect of modern business intelligence, we developed specific criteria for each in order to provide an in-depth look at features geared specifically to mobile, embedded and collaborative use.

We are happy to offer some insights on SAS drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements. Earlier this year we published the Ventana Research Value Index: Analytics and Business Intelligence 2019, the distillation of a year of market and product research efforts by Ventana Research. We then developed three additional Value Indexes on Analytics and BI focusing on mobile, embedded and collaborative capabilities. Because each is a critical aspect of modern business intelligence, we developed specific criteria for each in order to provide an in-depth look at features geared specifically to mobile, embedded and collaborative use.

We are happy to offer some insights on Yellowfin drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements. Earlier this year we published the Ventana Research Value Index: Analytics and Business Intelligence 2019, the distillation of a year of market and product research efforts by Ventana Research. We then developed three additional Value Indexes on Analytics and BI focusing on mobile, embedded and collaborative capabilities. Because each is a critical aspect of modern business intelligence, we developed specific criteria for each in order to provide an in-depth look at features geared specifically to mobile, embedded and collaborative use.

We are happy to share some insight on Domo drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements. Earlier this year we published the Ventana Research Value Index: Analytics and Business Intelligence 2019, the distillation of a year of market and product research efforts. We then developed three additional Value Indexes on Analytics and BI focusing on mobile, embedded and collaborative capabilities. Because each is a critical aspect of modern business intelligence, we developed specific criteria for each in order to provide an in-depth look at features geared specifically to mobile, embedded and collaborative use.

We are happy to offer some insights on SAP drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements. Earlier this year we published the Ventana Research Value Index: Analytics and Business Intelligence 2019, the distillation of a year of market and product research efforts. We then developed three additional Value Indexes on Analytics and BI focusing on mobile, embedded and collaborative capabilities. Because each is a critical aspect of modern business intelligence, we developed specific criteria for each in order to provide an in-depth look at features geared specifically to mobile, embedded and collaborative use.

We are happy to share some insight on BOARD drawn from our Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements. Earlier this year we published the Ventana Research Value Index: Analytics and Business Intelligence 2019, the distillation of a year of market and product research efforts. We then developed three additional Value Indexes on Analytics and BI focusing on mobile, embedded and collaborative capabilities. Because each is a critical aspect of modern business intelligence, we developed specific criteria for each in order to provide an in-depth look at features geared specifically to mobile, embedded and collaborative use.

We are happy to share some insights on Infor based on our latest market Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements. Earlier this year we published the Ventana Research Value Index: Analytics and Business Intelligence 2019, the distillation of a year of market and product research efforts. We then developed three additional Value Indexes on Analytics and BI focusing on mobile, embedded and collaborative capabilities. Because each is a critical aspect of modern business intelligence, we developed specific criteria for each in order to provide an in-depth look at features geared specifically to mobile, embedded and collaborative use.

We are happy to share some insights about IBM drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

We are happy to offer some insights on MicroStrategy drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements. Earlier this year we published the Ventana Research Value Index: Analytics and Business Intelligence 2019, the distillation of a year of market and product research efforts. We then developed three additional Value Indexes on Analytics and BI focusing on Mobile, Embedded and Collaborative capabilities. Because each is a critical aspect of modern business intelligence, we developed specific criteria for each in order to provide an in-depth look at features geared specifically to mobile, embedded and collaborative use.

We are happy to offer some insights on Information Builders drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements. Earlier this year we published the Ventana Research Value Index: Analytics and Business Intelligence 2019, the distillation of a year of market and product research efforts. We then developed three additional Value Indexes on Analytics and BI focusing on mobile, embedded and collaborative capabilities. Because each is a critical aspect of modern business intelligence, we developed specific criteria for each in order to provide an in-depth look at features geared specifically to mobile, embedded and collaborative use.

Qonnections 2019 is Qlik's annual user conference. Key news from this year's conference centered on acquisitions of Podium Data and Attunity, along with an expansion of certifications on Google Cloud Platform, AWS, and Azure, with the ability to support Red Hat OpenShift. Many of these announcements were centered on a key theme of a cloud and SaaS-first approach.

I am happy to offer some insights on Qlik drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for analytics and business intelligence. We evaluated Qlik and 14 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on analytics and business intelligence.

I am happy to offer some insights on Microsoft drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for analytics and business intelligence. We evaluated Microsoft and 14 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on analytics and business intelligence.

I am happy to offer some insights on Looker drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for analytics and business intelligence. We evaluated Looker and 14 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on analytics and business intelligence.

I am happy to offer some insights on Tableau drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for analytics and business intelligence. We evaluated Tableau and 14 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on analytics and business intelligence.

I am happy to offer some insights on Oracle drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for analytics and business intelligence. We evaluated Oracle and 14 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on analytics and business intelligence.

I am happy to share some insights gleaned from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Embedded Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. Drawing on our benchmark research and expertise, we apply a structured research methodology built on evaluation categories that are designed to reflect the real-world criteria incorporated in a request for proposal to vendors in analytics and business intelligence. Using this methodology, we evaluated vendor submissions in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). This research-based index is the first such evaluation to assess the full business value of embedded analytics and business intelligence software. You can learn more about our Value Index as an effective vendor selection and RFI/RFP tool at https://www.ventanaresearch.com/value-indexes.

I am happy to offer some insights on Salesforce.com drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for analytics and business intelligence. We evaluated Salesforce.com and 14 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on analytics and business intelligence.

I am happy to share some insights gleaned from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Mobile Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. Drawing on our benchmark research and expertise, we apply a structured research methodology built on evaluation categories that are designed to reflect the real-world criteria incorporated in a request for proposal to vendors in analytics and business intelligence. Using this methodology, we evaluated vendor submissions in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). This research-based index is the first such evaluation to assess the full business value of analytics and business intelligence software. You can learn more about our Value Index as an effective vendor selection and RFI/RFP tool at https://www.ventanaresearch.com/value-indexes.

For analytics to be effective, they need to be available to line-of-business personnel as needed in their normal course of conducting business, which today means providing rich mobile access to analytics through phones and tablets to support a mobile workforce seeking to conduct business in any location at any time. Workers today expect these mobile capabilities, which means organizations must make choices to provide analytics and BI platforms that can deliver them.

I am happy to offer some insights on SAS drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for analytics and business intelligence. We evaluated SAS and 14 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on analytics and business intelligence.

I am happy to offer some insights on Yellowfin drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for analytics and business intelligence. We evaluated Yellowfin and 14 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on analytics and business intelligence.

I am happy to share some insight on Domo drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements.  The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for analytics and business intelligence. We evaluated Domo and 14 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on analytics and business intelligence.

I am happy to offer some insights on SAP drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for analytics and business intelligence. We evaluated SAP and 14 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on analytics and business intelligence.

I am happy to share some insight on BOARD drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for analytics and business intelligence. We evaluated BOARD and 14 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on analytics and business intelligence.

I am happy to share some insights on Infor based on our latest market Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for analytics and business intelligence. We evaluated Infor and 14 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on analytics and business intelligence.

I am happy to share some insights about IBM drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for analytics and business intelligence. We evaluated IBM and 14 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on analytics and business intelligence.

I am happy to offer some insights on MicroStrategy drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for analytics and business intelligence. We evaluated MicroStrategy and 14 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on analytics and business intelligence.

I am happy to offer some insights on Information Builders drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for analytics and business intelligence software. We evaluated Information Builders and 14 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on analytics and business intelligence.

I am happy to share some insights gleaned from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. Drawing on our benchmark research, we apply a structured research methodology built on evaluation categories that are designed to reflect the real-world criteria incorporated in a request for proposal to vendors in analytics and business intelligence. Using this methodology, we evaluated vendor submissions in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). This research-based index is the first such evaluation to assess the full business value of analytics and business intelligence software. You can learn more about our Value Index as an effective vendor selection and RFI/RFP tool at https://www.ventanaresearch.com/value-indexes/inclusion.

Ventana Research provides unique insight into the analytics and business intelligence (BI) industry. This is important, as its processes and technology play an instrumental role in enabling an organization’s business units and IT to utilize its data in both tactical and strategic ways to perform optimally. To accomplish this, organizations must provide technology that can access the data, generate and apply insights from analytics, communicate the results and support collaboration as needed.

FinancialForce offers cloud-based ERP and professional services automation (PSA) software. The company targets midsize and larger services companies, especially those that provide professional services (such as consultants or field service organizations), subscription-based or recurring revenue services. FinancialForce’s key point of differentiation is that it is built natively on the Salesforce platform. Thus, CRM data is already located on the same platform as accounting and back-office data so organizations can orchestrate end-to-end front-office to back-office processes without having to integrate different systems.

I am happy to share some insight on AWS drawn from our latest research. The Ventana Research Value Index: Contact Center in the Cloud in 2018 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for contact centers in the cloud. We evaluated AWS and 12 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on contact centers in the cloud. 

I am happy to share some insight on 8x8 drawn from our latest research. The Ventana Research Value Index: Contact Center in the Cloud in 2018 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for contact centers in the cloud. We evaluated 8x8 and 12 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on contact centers in the cloud. .

I am happy to share some insight on IFS-mplsystems drawn from our latest research. The Ventana Research Value Index: Contact Center in the Cloud in 2018 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for contact centers in the cloud. We evaluated IFS-mplsystems and 12 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on contact centers in the cloud.

I am happy to share some insight on Altitude drawn from our latest research. The Ventana Research Value Index: Contact Center in the Cloud in 2018 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for contact centers in the cloud. We evaluated Altitude and 12 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on contact centers in the cloud.

I am happy to share some insight on Five9 drawn from our latest research. The Ventana Research Value Index: Contact Center in the Cloud in 2018 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for contact centers in the cloud. We evaluated Five9 and 12 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on contact centers in the cloud.

I am happy to share some insight on RingCentral drawn from our latest research. The Ventana Research Value Index: Contact Center in the Cloud in 2018 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for contact centers in the cloud. We evaluated RingCentral and 12 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on contact centers in the cloud.

I am happy to share some insight on Content Guru drawn from our latest research. The Ventana Research Value Index: Contact Center in the Cloud in 2018 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for contact centers in the cloud. We evaluated Content Guru and 12 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on contact centers in the cloud.

I am happy to share some insight on NewVoiceMedia drawn from our latest research. The Ventana Research Value Index: Contact Center in the Cloud in 2018 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for contact centers in the cloud. We evaluated NewVoiceMedia and 12 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on contact centers in the cloud.

I am happy to share some insight on Serenova drawn from our latest research. The Ventana Research Value Index: Contact Center in the Cloud in 2018 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for contact centers in the cloud. We evaluated Serenova and 12 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on contact centers in the cloud.

I am happy to share some insight on Genesys drawn from our latest research. The Ventana Research Value Index: Contact Center in the Cloud in 2018 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for contact centers in the cloud. We evaluated Genesys and 12 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on contact centers in the cloud.

I am happy to share some insight on BroadSoft drawn from our latest research. The Ventana Research Value Index: Contact Center in the Cloud in 2018 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for contact centers in the cloud. We evaluated BroadSoft and 12 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on contact centers in the cloud.

I am happy to share some insight on Aspect Software drawn from our latest research. The Ventana Research Value Index: Contact Center in the Cloud in 2018 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for contact centers in the cloud. We evaluated Aspect Software and 12 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on contact centers in the cloud.

I am happy to share some insight on NICE inContact drawn from our latest research. The Ventana Research Value Index: Contact Center in the Cloud in 2018 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for contact centers in the cloud. We evaluated NICE inContact and 12 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on contact centers in the cloud.

I am happy to share some insights gleaned from our latest research. The Ventana Research Value Index: Contact Center in the Cloud in 2018 is the distillation of a year of market and product research efforts by Ventana Research. Drawing on our benchmark research, we utilize a structured research methodology with evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal to vendors in contact centers in the cloud. Using this methodology, we evaluated vendor submissions in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). This research-based index is the first such industry undertaking to assess the full business value of software designed for enabling a contact center in the cloud. You can learn more about our Value Index as an effective vendor selection and RFI/RFP tool at https://www.ventanaresearch.com/value-indexes/inclusion.

An intensified focus on the customer is driving the trend toward enabling omnichannel support in contact centers, our benchmark research on contact centers in the cloud has found. In my last analyst perspective I highlighted some key benefits of a contact center in the cloud. In this perspective, I want to elaborate on the finding that only about one-third (35%) of organizations participating in our benchmark research said their customers are satisfied with the way interactions are handled. Far more (47%) said their customers are only somewhat satisfied, which may not be good enough in a fiercely competitive marketplace. Not surprisingly, improving the customer's experience is the most common motivator (cited by 82%) for change in the technology being used.

To remain competitive, organizations must deliver the best possible customer experience through all channels of engagement. One technological approach to accomplish this is to enable a contact center to handle all the channels through which customer interactions with the organization are routed and acted upon. The contact center continues to need to handle telephony, of course, as this remains a channel that carries a significant portion of interactions. But new channels continue to be added to the interaction mix. With the advent of cloud computing, enabling systems and technologies to be managed on the Internet rather than on the premises of an organization, contact centers can be established and interaction channels can be added and configured far more easily.

Workday will acquire Adaptive Insights for $1.55 billion in cash, with the transaction scheduled to close in the third quarter of this year. The combination adds Adaptive Insight’s well-developed cloud-based financial performance management software to Workday’s workforce and financial management suite. Workday says Adaptive will operate as a standalone business and continue with its current product strategy.

Employee engagement has been a dominant theme in both human capital management (HCM) and the systems to manage it in recent years; lately (though not necessarily appropriately) it is a topic often equated with the notion of the employee experience. On a related point, Gallup’s annual employee engagement survey has consistently found the majority of today’s workforce to be disengaged, defined as “not enthusiastic or passionate about their work.” Interest in the degree to which HCM technology can improve employee engagement (or mitigate disengagement) now rivals the attention given to such perennial chief human resources officer (CHRO) concerns as attracting and retaining top talent and retooling the workforce.

We now are well beyond the year depicted in 2001: A Space Odyssey, a cinematic perspective on the future of artificial intelligence in which HAL 9000, a computer, is able to simulate human behavior and control machines. Anyone reviewing the past two years of marketing around AI in the business technology industry can be forgiven for believing that we have arrived at the futuristic state Stanley Kubrick imagined. We have not.

Blockchains are attractive because their built-in security and trust factors make them useful for almost all business interactions involving organizations and individuals. Blockchains have two basic functions. One is as a method for handling transactions involving property such as land deeds, trademarks or other assets. The second involves exchanges of data such as identities of individuals or businesses, the location of an object at a point in time or weather conditions. All interactions involving property or assets include the transfer of data as well, of course, but some blockchain use cases are informational only.

Workday recently presented a technology summit for industry analysts. The presentations focused on Workday’s ongoing product advancements as well as its approach to employing emerging technologies. These technologies include artificial intelligence (AI) and machine learning (ML), robotic process automation (RPA) and bots utilizing natural language processing. Ventana Research uses the term “robotic finance” to refer to these technologies when used in the office of finance. In our view, they will have a profound impact on the nature of white-collar work over the coming decade. Financial management and ERP software vendors are focusing on these technologies because they will disproportionately affect finance and accounting departments: I estimate that their adoption has the potential to eliminate one-third of the accounting department’s workload within a decade.

We are have arrived at the May 25, 2018 date when the European Union’s General Data Privacy Regulations (GDPR) become enforceable, following what has been a two-year transition period. Companies were given this time to put in place reasonable measures and the systems necessary to support the legislation’s wide-ranging personal data privacy requirements, which apply to any organization with more than 250 employees that serves EU citizens. While this regulation will apply in the EU, it has implications for any organization in the world that provides services involving the personal data of any EU citizen.

Advancing the potential of any business requires continuous improvement in the processes and technology that support it. Many companies have embraced attempts at a digital transformation, and it’s become a goal to which organizational resources and budgets have been dedicated around the globe.

After more than a decade of steady development, ERP systems today are changing fundamentally, facilitated by the availability of advances such as cloud computing, advanced database architecture, collaboration, improved user-interface design, mobility, analytics and planning. This was evident when Oracle recently held its third analysts-only ERP Cloud Summit in New York to coincide with its Modern Finance Experience event. Oracle now has an increasingly robust set of business applications that reside in the cloud and a growing list of live customers – large and midsize – from a range of industries across the world, both of which were offered as part of the here-and-now technology theme at the event.

I’m thrilled to announce to my HCM vendor and practitioner network as well as the ever-expanding Ventana Research community that I’m now directing Ventana’s HCM practice. I will be working closely with our CEO and Chief Research Officer Mark Smith, who is a fellow HCM enthusiast and thought leader.

Oracle OpenWorld is a fall event that sprawls over a lot of territory – figuratively in terms of the IT landscape and, if you’re in San Francisco, literally. My focus here is on the ERP portion of the company’s software portfolio.

Sage Intacct recently held its annual user group meeting. The cloud financial management software service provider targets rapidly growing small- and midsize services companies. Within this broad category, Sage Intacct focuses on verticals including software, financial services, healthcare, nonprofits, wholesale and franchisers.

In 2016 Unit4 acquired Prevero, a financial performance management software company. The acquisition reflects a trend toward the convergence of transactional and analytical business applications. ERP and financial management software vendors increasingly are adding analytic capabilities – especially in financial performance management (FPM) – to the core functions of transaction processing and accounting in order to broaden the scope of their offerings. The integration of transaction processing and analytical software is especially valuable to Unit4’s core customer base of midsize organizations, which we define as those with 100 to 1,000 employees. Midsize entities have almost the same systems requirements as larger ones but lack the resources the latter enjoy.

Today many conversations about contact centers and CRM focus on customer engagement and the customer experience. Customer engagement should be relatively straightforward, addressing how organizations interact with customers through different channels of engagement. However, when it comes to customer experience, I believe many miss the point. The key word is experience, which means it is ultimately about perceptions and emotions. Companies must consider how customers feel prior to, during and after interactions. A common example would be a customer who feels frustrated when he or she gets a bill and believes it is wrong, who then gets angry talking to an agent who can do nothing about it and, as a result, considers changing suppliers.

Our benchmark research into next-generation customer engagement finds that three-quarters (77%) of organizations participating in the research said it is very important to improve the way they engage with customers. The two main drivers behind this are improving the customer experience (cited by 74%) and im­proving performance of the custo­mer service organization (70%). This is important because most companies said their customers have good experiences, but only one-third said that experience is excellent.

If we look at the focus of technology vendors for analytics and business intelligence or business applications providers deploying these capabilities in the last five years, we see that they have elevated the importance on the value of visualization and dashboards. These promotions might be understandable, but will they make business and the people using them more intelligent?

More than a year ago I wrote from personal experience about the challenges our firm encountered with Salesforce’s cloud computing systems and customer service and if we can trust them for business in the cloud. That perspective covered a range of issues that the behemoth cloud computing applications and platform company is facing regarding its service and technology. While Salesforce has shifted its customers like us and others to a different cloud computing environment, as it did in moving us off its #NA14 cloud computing instance, core challenges of its customer experience and billing processes persist. After the last customer experience incident, I contacted its executives about the need for operational improvement; it was clear in the dialogue that they saw some but not all of our experience as issues important to improving its customer processes. It was good to get some immediate attention, but my hope was to speak for all SMB companies in pointing out the importance of effective communications and escalating notifications and interactions when those customer moments go sour, so the customer isn’t forced to turn to social media to be heard. This was an area where Salesforce had significant room for improvement in customer engagement, reflecting a pattern we see in our benchmark research, which finds the most common challenges in almost half of organizations are integration of channels of engagement and managing activities as silos.

I recently attended SuiteWorld, NetSuite’s annual user conference. In the opening keynotes and throughout the event speakers emphasized benefits for NetSuite users resulting from the merger of NetSuite and Oracle, completed last fall. I wrote about this at the time. NetSuite users are likely to benefit from Oracle’s sales and core technology infrastructure. Before the merger, NetSuite’s R&D spending was constrained by being a public company. The amounts needed to rebuild and extend its software on an accelerated timetable likely would not have been acceptable to stock market investors.

This year various types of organizations are embracing machine learning like it is going out of style – or maybe it would be better to say coming into style. And now with a little investigation on LinkedIn finds over half million professionals with machine learning in their job title. Machine learning is the application of specific data science algorithms that become more accurate as the system records more outcomes and processes more data. This improvement is referred to as “learning,” hence the name. There are good reasons machine learning is growing so rapidly, but there are pitfalls to avoid as well.

Informatica reintroduced itself to the world at its recent customer conference, Informatica World, in San Francisco. The company took advantage of the event to showcase its new branding in an effort to change the way customers think about the company. Informatica has been providing information services in the cloud for more than a decade. Even though cloud revenue comprises a minority of Informatica’s business, in absolute terms, the revenue is significant, and company executives want the public to recognize Informatica as a leader in cloud-based data management services for enterprises. Presenters also made notable product announcements, discussed below, including the application of machine learning to the data management process.

Our firm regularly explores the impacts of new technologies on business. Analytics is foremost among recently emerging technologies, which our benchmark research consistently confirms. In our research on next-generation sales analytics, fourth-fifths (82%) of participating organizations cited analytics as the most important technology trend for sales; however, several other technologies also are adding power and flexibility to the use of sales analytics.

Vendavo recently held its annual Profit Summit, a combination of a user group conference and a forum for covering evolving trends and techniques in business-to-business (B2B) pricing. Especially in emerging categories like pricing and revenue management, this sort of event provides an opportunity to assess the state of the market and the maturity of the applications. As I’ve noted, adoption of price and revenue management software has been slow in the B2B segment of commerce due to multiple obstacles. The challenges include change management, as well as data and process issues.

The importance of analytics for sales organizations is clear and, as I pointed out in my recent analyst perspective on the next generation of sales analytics, these capabilities optimize revenue potential. However, utilizing sales analytics requires a set of data skills that most organizations still find challenging and are thus not fully prepared to support. The efficient access and preparation of data underlies any analytics processes, which must meet demanding needs that are not always automated. Our research into next generation sales analytics has found many impediments that must be addressed and is a critical part of our expertise agenda for sales organizations.

I have been following advances in sales analytics since the 1990s. Over the last five years, however, I have seen evolution, not innovation. In most cases the information that analytics provides is too complicated and not contextualized enough for sales people who are not analytics experts to understand, let alone take action on. As I pointed out in my 2017 research agenda on sales, analytics is essential for planning that improves the impacts of sales efforts and meets the goals of the organization.

Anaplan recently held Anaplan Hub, its annual user group meeting. The company offers a cloud-based business planning platform that incorporates a modeling and calculation engine. The tool makes it relatively easy to add or expand the scope of plans that can be connected and monitored as a central source. Companies typically use Anaplan software for financial planning or budgeting, sales, workforce, marketing and IT planning. These are the types of plans in which companies often need to create models that incorporate their specific requirements, their strategy and their business systems.

Some 3,000 people attended Domo’s recent customer event, called Domopalooza. That’s nearly double the attendance of the previous event, which my colleague Mark Smith covered. Formerly a bit “stealthy,” Domo has started sharing more information, some of which I’ll pass along, as well as observations about product announcements made at the event.

In tracking Genesys for several years I have seen it grow through a series of product developments and acquisitions – from predominantly selling call routing and computer/telephony integration (CTI) software to providing a suite of products that manage inbound and outbound, assisted and digital channels of customer engagement. Continuing this expansion Genesys recently acquired Interactive Intelligence and Silver Lining. These new assets signal another round of transformation as the company builds support for what I call a customer experience hub – a combination of products to support all aspects of enterprise-wide customer engagement.

Ventana Research recently announced the results of its latest Benchmark Research, Next-Generation ERP. The enterprise resource planning (ERP) system is at the core of nearly every company’s record-keeping and management of business processes. Its smooth and uninterrupted functioning is essential to an organization’s accounting and finance functions. In manufacturing and distribution, ERP manages inventory and logistics. Some companies use it to handle human resources functions like tracking employees, payroll and related costs.

I recently attended SAS Institute’s analyst relations conference. There the company provided updates on its financial performance and its Viya platform and a glimpse into some of its future plans.

Cloudera provides database and enabling technology for the big data market and overall for data and information management. As my colleague David Menninger has written, the big data and information management technology markets are changing rapidly and require vendors to adapt to them. Cloudera has grown significantly over the last decade and now has approximately 1,000 customers and provides support and services in countries around the world. Its product and technology strategy is to provide a unified data management platform, Cloudera Enterprise, that can meet the data engineering and science needs for a range of analytic and operational database applications. Its primary focus is its Enterprise Data Hub, which as a data lake can handle organizations’ big data and analytical needs. As David Menninger asserts, the data lake is a safe way to invest in big data. It also helps shift the focus  away from the V’s (volume, velocity and variety) of big data to the A’s, which are analytics, awareness, anticipation and action.

Business process reengineering was a consulting fashion in the early 1990s that spurred many companies to purchase their first ERP systems. BPR proposes a fundamental redesign of core business processes to achieve substantial improvements in market and customer responsiveness, productivity, cycle times and quality. ERP systems support business process reengineering by guiding the step-by-step execution of the redesigned process to ensure that it is performed consistently. They also automate the handoffs between individuals and departments to accelerate completion of that process.

In tracking NICE for a decade I have seen the company grow, through a series of acquisitions and product developments, from a vendor largely of workforce management systems to one that offers a full suite of workforce optimization products. It is now advancing what I call a customer experience platform that builds on top of my last coverage of it advancing its efforts. This includes systems to manage assisted channels of engagement (primarily the telephone), digital channels of engagement, workforce optimization, advanced analytics and tight integration with business applications such as CRM. NICE is on the road to building such a platform using existing and newly developed products and those that it recently acquired from Nexidia and inContact. It will take time before a fully integrated platform is available, but the company has already taken steps toward this goal.

I am happy to provide my personal perspective on the potential of sales organizations, processes and technology to supercharge business activity in 2017. The sales processes of organizations – whether they involve digital commerce or direct or indirect physical selling – should be part of continuous optimization efforts to reach maximum results. To do this, the people leading and running sales processes must be able to use technology that supports their responsibilities and analyzes the crucial information coming into the business. For almost 15 years, we have advocated for sales applications and tools that are necessary to optimize sales effectiveness and improve the outcomes of their sales efforts. The available portfolio is much larger than sales force automation (SFA) and involves more than the continued use of CRM, which has clear limits in its ability to manage customer relationships. The applications on offer include many facets of sales:  coaching, compensation management, contract management, configure price quote (CPQ), forecasting, quota and territory management, planning and optimization, pricing and revenue optimization, and target or market intelligence. New applications designed for sales also enable digital effectiveness that can transform organizations. Let me provide my perspective on six topics that are shaping the way sales can and should operate in 2017, and which are part of our sales research agenda for the year.

More businesses are using software to implement and support a strategic pricing strategy designed to optimize revenue and margins in business-to-business (B2B) transactions because it can help improve results at the bottom line. “Optimize” in this instance means managing the trade-off that usually exists between revenue and profitability objectives in order to support a company’s strategy and capabilities in a given market. Business-to-business pricing management is Ventana Research’s term for such processes and applications. Software built for this purpose centralizes control and enforces consistency in pricing while assisting sales agents in negotiating prices that achieve desired business objectives. It enables agents to use techniques that can increase the revenue from a transaction, the margin on the sale or the probability of closing the sale.

Until recently most organizations deployed systems on their own premises to build communications and contact center infrastructures, which often required them to integrate products from several vendors. In the past few years many vendors have moved their systems to the cloud, and others have begun as cloud-based suppliers. This trend has opened up the opportunity for more organizations to take advantage of modern communication systems and contact centers. Using the cloud for either, or both can save money and resources, reduce risk, and make available more integrated, multi-channel systems.  While the adoption of such systems has undoubtedly increased and is likely to continue to do so, our benchmark research into next-generation contact centers in the cloud finds that many organizations still prefer to remain on premises, and adoption of cloud-based systems occurs on a case-by-case basis. In addition, many organizations look for vendors that support multiple models so they have the option of starting out using one model but transitioning later to another, including to a hybrid model in which some systems are on-premises and others are cloud-based..

Senior finance executives and finance organizations that want to improve their performance must recognize the value of technology as a key tool for doing high-quality work. Consider how poorly your organization would perform if it had to operate using 25-year-old software and hardware. Having the latest technology isn’t always necessary, but it’s important for executives to understand that technology shapes a finance organization’s ability to improve its overall effectiveness.

In 2016 Ventana Research saw a significant shift in the customer engagement and contact center software markets. Our benchmark research into the next-generation contact center in the cloud shows that for 70 percent of companies, customer experience is and will be an important way of competing; the largest growth in ways of competing is to introduce digital self-service, which will increase by 12 percent. To support those changes, organizations have introduced more channels of engagement, to the extent that our research shows the average has grown to eight channels. Our benchmark research into next-generation customer engagement shows that in nearly half (47%) of organizations these channels are managed as silos, which indicates that most organizations still operate multiple channels rather than supporting omnichannel engagement. The next-generation contact center research confirms that customer engagement is an enterprise-wide issue but one-third (33%) of companies struggle to provide consistent responses across touch points.

Ventana Research analysts recently published our research agendas for 2017. As we put together these plans we think about the forces that are shaping the markets that we cover and then craft agendas that study these issues to provide insights for our community. I’ve been working in the business intelligence (BI) and analytics market for nearly 25 years, and throughout that time the industry has been trying to make analytics useful to increasingly wider audiences. That focus continues to today. Better search and presentation methods, including visual discovery and natural-language processing, are promising ways to engage more users. We also see organizations supporting their users in specific functional roles with relevant and accessible analytics. My colleagues examine these issues as part of their agendas in the Office of Finance, Sales, Marketing, Customer Experience, Operations and Supply Chain, and Human Capital Management. While their agendas include analytics within specific domains, my own research focuses on a range of analytics issues across domains including cloud computing, mobility, collaboration, data science and the Internet of Things.

Price and revenue optimization (PRO) is a business discipline used to produce demand-based pricing; it applies market segmentation techniques to achieve strategic objectives such as increased profitability or greater market share. In essence, PRO enables companies to surf the demand curve using dynamic rather than fixed pricing to achieve the most desirable trade-offs between revenue volume and profit margins. The trade-off is defined by strategic factors such as the company’s market position, product and service portfolio, and marketing strategy.

Over the last few years the telecommunications and call center industries have undergone radical changes. Telecommunications was mainly in the hands of national and regional telecom companies, which essentially owned all the cables in the ground. The call center market was dominated by a small number of vendors that provided on-premises systems to manage and route calls when they arrived at a company’s offices. The telecom model was in effect the first cloud-based service, though almost no one stopped to think about how a call made on one device arrived at another. The arrival of the internet and wireless technologies and the telecom companies’ willingness to lease capacity on their lines changed both models. Now almost any company can provide communication services, and the majority of contact center systems are cloud-based. In this evolution some organizations that previously were hidden behind the telecoms have emerged as suppliers of communications and contact center services.

Our benchmark research into the next-generation contact center in the cloud confirms what most people intuitively know – that consumers now engage with each other and organizations through more communication channels than a few years ago and that many of these are speech- and text-based. Companies are therefore generating large volumes of voice recordings and textual records. They contain vital information about what customers feel about issues connected to their dealings with the organization – marketing messages the sales process, product and service quality, and employee behavior, among others. The challenge for organizations is to extract insights from these unstructured records and take action to benefit the business based on those insights. When it was founded in 2002, CallMiner set out to support organizations in that quest, and in 2012 it won a Ventana Research Technology Innovation awards.

Zuora provides software that supports the rapidly expanding subscription economy. I recently attended the company’s user event in London, called subscribe16. During his keynote speech CEO Tien Tzuo insisted that the subscription economy is not only here to stay but is likely to grow substantially. In the U.K. alone, he said, 40 million users are using subscription services, including 14 million use video streaming services, 5.4 million use music streaming services, and perhaps most surprising, 78 percent of adults age 55 or older use at least one subscription service.

Today’s rapid changes in technology have left many companies behind in the digital transformation that is shaping the future of marketing, sales, commerce and client engagement. At Ventana Research we have seen this change coming, having been close observers and analysts of technological shifts for almost 15 years, providing continuous research and guidance to the technology industry. Now the leading edge is the digital point of engagement with customers through websites and social media. Earlier this year I wrote about mastering marketing mayhem in a meaningful, meticulous manner explaining how organizations can adapt to the new digital reality. Well, we are taking our own advice. Ventana Research spent the first half of 2016 reflecting on lessons learned and best practices from our research and advisory efforts. The result is our new community and website, www.ventanaresearch.com that we have announced and is available for everyone on the Internet. With it we strive to set an example of simplicity in engaging an audience in need of insights and education on technology applied to business.

IBM recently held its inaugural World of Watson event. Formerly known as IBM Insight, and prior to that IBM Information on Demand, the annual event, attended by 17,000 people this year, showcases IBM’s data and analytics and the broader IBM efforts in cognitive computing. The theme for the event, as you might guess, was the Watson family of cognitive computing products. I, for one, was glad to spend more time getting to know the Watson product line, and I’d like to share some of my observations from the event.

Verint is an established vendor of contact center systems. Its portfolio of products includes digital customer engagement, knowledge management, agent desktop, workforce optimization (for which it was recently rated the top vendor in the Ventana Research 2016 Value Index), voice of the customer and multiple forms of analytics - including text. Verint has built its portfolio through internal developments and acquisitions, the latest of which is OpinionLab. This merger adds two significant capabilities to its already extensive voice of the customer capabilities, giving organizations the ability to measure customer feedback across all channels, including digital.

Robotics is nothing new to some aspects of manufacturing and the IT industry, but it is relatively new in the customer experience (CX) market. The term often conjures up images of little gray machines taking over tasks previously handled by humans – machines making cars, programmed vacuum cleaners and the like. In the CX space, however, we are not talking about machines but about software that can automate routine tasks. For the time being, I don’t believe robots will take over the contact center and replace human agents. Indeed our recent research into next-generation contact centers in the cloud strongly suggests the opposite. It shows that the telephone is still the top channel of communication and that almost two-thirds (62%) of organizations expect call volumes to rise over the next 24 months. Thus agents will continue to handle large volumes of interactions, which may become more complex.

Analysts have been talking and writing about a “360 degree” view of the customer for years. Our own benchmark research into customer relationship management shows that only37 percent of organizations are able to produce analysis and reports that yield such a comprehensive view. Other research into next-generation customer analytics reveals that the main issue in this area for nearly two-thirds (63%) of organizations is data availability. To make the situation worse, customer-related data is getting ever more numerous and complex. A principal reason for this growth is the number of communication channels consumers now use to engage with organizations and the type of data these channels produce. It includes call recordings, text messages, email, social media posts, customer feedback surveys, chat scripts and event data such as videos that users download. All of these types of data are unstructured , which makes them harder for conventional analytics tools to access and analyze.

SYSPRO is a 35-year-old software vendor that focuses on selling enterprise resource planning (ERP) systems to midsize companies, particularly those in manufacturing and distribution. In manufacturing, SYSPRO supports make, configure and assemble, engineer to order, make to stock and job shop environments. The company attempts to differentiate itself through vertical specialization and its years of ongoing development, which can reduce the need for customization and cut the cost of initial and ongoing configurations to suit the needs of companies in these industries, thereby reducing the total cost of ownership. Worldwide its targeted verticals include electronics, food, machinery and equipment and medical devices; in the United States, SYSPRO adds automotive parts (original equipment and after-market) and energy. The company’s development efforts follow a design philosophy that balances its target customers’ need for software capabilities that are on par with larger enterprises with their resource constraints (chiefly limited financial resources and technical staffs).  Its software can be deployed on-premises or in the cloud.

In the late 1990s, CRM systems were launched to help organizations become customer-centric, to manage customer relationships from end to end, through marketing to sales to customer service, and to provide a “360-degree view of the customer.” For a variety of reasons (overselling, lack of proper adoption, missing functionality), they never lived up to many companies’ expectations, and so CRM got a poor reputation. I recently wrote that customer experience management has undergone significant change in the last 18 months, taking over the role of helping organizations become customer-centric, and that CRM vendors have played a part in these changes. Some of the larger ones have, in my view, taken a backward step by breaking CRM into three components to support marketing, sales and customer service; this makes it harder to support the end-to-end customer life cycle.

During a recent briefing with NGData, I was initially put off by excessive “marketing speak.” The team began by describing its product, Lily Enterprise, as a “customer experience operating system.” Being used to having operating systems run entire computers, I wasn’t sure what this meant. This term was followed by a statement that NGData’s products help companies transition from being “B2C to C2B,” that is, to put the customer first, an idea that has been around for several years but in my experience few companies achieve. One of the biggest challenges in this regard is that most companies are organized into business groups, and each business group typically has its own processes, systems and metrics, a situation that makes it hard to have a single view of the customer and take actions based on the same customer view, and which lends itself to focusing on internal goals, not the customer. As an example, our research into next-generation customer engagement shows three key impediments to delivering exceptional customer experiences: systems that are not integrated (for 49% of organizations), communication channels managed as silos (47%) and customers receiving inconsistent responses at different touch points. The root cause of all these is data – customer data. Organizations have multiple systems that generate customer data, in multiple forms: for example, structured data in CRM and ERP systems, voice recordings, text data from multiple sources (letters, email, Web scripts, text messages, chat scripts and social media posts), video and event data such as a customer downloading a film. With so much data in so many formats, it is hard for companies to generate a single, “360 degree” view of the customer that can be shared across the whole organization.

Over the years, our benchmark research studies on contact center systems have shown that larger centers use dedicated contact center systems to support their operations nearly twice as often as centers that have fewer than 250 seats. Smaller centers typically lack budgets and technical skills to deploy and operate such systems. This situation is evident in the tools commonly used to support workforce management and analytics; smaller centers most often use spreadsheets. While spreadsheets have their place in limited ad hoc analysis for small groups, in an environment such as a contact center, they cause issues with regard to ingesting data from multiple sources and providing analysis in real time.

I recently attended Oracle OpenWorld for the first time in several years. The message at this year’s event was clear: Oracle is all in on the cloud. I had heard the message, but I didn’t get the full impact until I arrived at the Moscone Center in San Francisco. All signage at the event contained the word “cloud,” and Oracle issued 18 press releases in conjunction with OpenWorld related to cloud computing. I also found out that Oracle has its own definition of “cloud.”

The annual Oracle OpenWorld user group meeting provides an opportunity to step back and take a longer view of business, industry and technology trends affecting the company. Last year, after listening to Larry Ellison’s and Mark Hurd’s vision for the future of IT, I wrote that Oracle had to continue shifting its focus to business applications because the accelerating shift to cloud computing would lead corporations to outsource their IT infrastructures, services and security to third parties. Eventually, this would substantially shrink the market for corporate IT departments, which has been Oracle’s strength. At this year’s conference the company demonstrated how it is applying its technology strengths to create a competitive advantage that it can apply to its broad business applications portfolio.

I recently attended Oracle OpenWorld for the first time in several years. The message at this year’s event was clear: Oracle is all in on the cloud. I had heard the message, but I didn’t get the full impact until I arrived at the Moscone Center in San Francisco. All signage at the event contained the word “cloud,” and Oracle issued 18 press releases in conjunction with OpenWorld related to cloud computing. I also found out that Oracle has its own definition of “cloud.”

I have been involved in the call center and customer engagement market for more than 25 years, first as a consultant and systems integrator and for the past 11 years as an industry analyst. There have been lots of changes in that time but never as many as in the last 12 to 18 months. A simple illustration of the change is how I group vendors.

Like many other industry observers I’ve heard overblown claims for information technology for decades. However, I’ve also observed that – eventually – reality catches up with vision. Finance and accounting departments are particularly resistant to change, yet because almost no corporations use adding machines or typewriters any more, it’s clear that transformative change can happen. Nonetheless, because users of business computing systems are inundated with “it’s better than ever” promotions by vendors, journalists and industry analysts, may have grown jaded and disbelieving. In the case of ERP systems that help run many organizations, that is too bad because we are finally at the point of a fundamental change in this business-critical software category.

Teradata recently held its annual Partners conference, at which gather several thousand customers and partners from around the world. This was the first Partners event since Vic Lund was appointed president and CEO in May. Year on year, Teradata’s revenues are down about 5 percent, which likely prompted some changes at the company. Over the past few years Teradata made several technology acquisitions and perhaps spread its resources too thin. At the event, Lund committed the company to a focus on customers, which was a significant part of Teradata’s success in the past. This commitment was well received by customers I spoke with at the event.

Ventana Research has published its Workforce Optimization 2016 Value Index. The Value Index provides a comprehensive evaluation of contact center workforce optimization vendors based on responses to our RFP-like questionnaire, which was constructed using insights gained from our recent benchmark research into workforce optimization and our knowledge of the market. In our definition workforce optimization systems include interaction recording, agent quality management, workforce management, agent compensation management, training and coaching, and interaction-handling analytics. The research shows that organizations have deployed many of these applications and by doing so have achieved efficiencies in handling interactions, improved outcomes of those interactions and improved both customer and employee satisfaction.

It often seems to business-to-business (B2B) marketers as if the only people who understand them are other B2B marketers. They feel that salespeople don’t get what they do day-to-day, that friends and family don’t understand what they do for a living, and most of all that the executives to whom they report have no interest in what they do – that is, until the last day of the quarter. Then they require that B2B marketers deliver positive, lead-generating and revenue-producing results in reports that detail how their efforts supported sales in the previous 90 days. And they expect those results to be reported in a format understandable to all.

Invoicing and billing are mundane business activities that hardly anyone outside of the accounting department cares about, but they are where the back office meets the front office. How well a company handles the process of getting paid by its customers can have an impact on its relationships with them. Like most of the details of business process execution, the impact of substandard invoicing and billing is rarely obvious or even of interest to senior management. That said, like trimming scrap rates or increasing sales pipeline conversion rates by a couple of percentage points, achieving consistent incremental gains in the “little stuff” of business usually translates into greater competitiveness and better financial performance.

In July Salesforce officially closed on its purchase of digital commerce platform provider Demandware for US$2.8 billion. Salesforce’s executives were interested in acquiring a digital commerce platform, and they claim that Demandware was routinely mentioned in their due diligence of the market. So out came Marc Benioff’s and Salesforce checkbook, and they paid. Handsomely. For that sizeable investment, Salesforce will add Demandware’s SaaS-delivered digital commerce capabilities to its Customer Success Platform, while Demandware customers will have access to the Salesforce suite of cloud-based sales, marketing, customer service and analytics tools. But savvy business and IT customers are not getting distracted by the details of this transaction or the acquisition’s market impact. Knowledgeable executives expected a significant deal like this for Salesforce, and they were already thinking ahead of laggards who are just now assessing the implications of this transaction.

Today’s proponents of artificial intelligence (AI) tend to focus on its spectacular uses such as self-driving cars and uplifting ones such as medical treatment. AI also has the potential to aid humanity in more modest ways such as eliminating the need for individuals to do tedious repetitive work in white-collar areas. Along these lines, at its recent Vision users conference, IBM displayed an application of its Watson cognitive computing technology designed to automate important aspects of regulatory and legal compliance. Should it prove workable, the application of cognitive computing to compliance could be the first step in achieving what various “Paperwork Reduction Act” legislation has failed to do: substantially cutting the time needed to comply with rules imposed by government entities.

I recently wrote that companies are struggling to provide omnichannel customer experiences and digital customer service is now seen as a business differentiator. To address these issues, organizations need to  change how they use people and processes, and deploy innovative technologies that can support new initiatives. To provide an enterprise-wide solution, contact center systems fall into four categories: communications, business applications, analytics and self-service. Our benchmark research into next-generation contact center systems in the cloud shows which types of systems companies have deployed, which they plan to deploy in the next 24 months and whether they prefer them to be on-premises or cloud-based.

In today’s intensely competitive markets, companies must strive to meet customer expectations during every interaction, and interactions occur through many channels. Our benchmark research into next-generation customer engagement finds that customers use up to 17 channels of engagement. Some channels involve assisted service from employees of the company, and some use self-service technologies such as interactive voice response (IVR), websites, mobile apps and social media, also known as digital service. Although the use of self-service is increasing, the research finds that organizations still expect volumes of assisted interactions to grow, albeit more slowly. The research also shows that the employees customers interact with may work in almost any line of business, including marketing, sales, the contact center, finance and human resources. These challenges require organizations to focus on people, processes, information and technology to optimize the performance of the workforce.

Predictive analytics is a rewarding yet challenging subject. In our benchmark research on next-generation predictive analytics at least half the participants reported that predictive analytics allows them to achieve competitive advantage (57%) and create new revenue opportunities (50%). Yet even more participants said that users of predictive analytics don’t have enough skills training to produce their own analyses (79%) and don’t understand the mathematics involved (66%). (In the term “predictive analytics” I include all types of data science, not just one particular type of analysis.)

Businesses and customers are ready for a new generation of digital commerce technology, but implementing it is challenged by significant barriers in two basic categories: technology commoditization and the lack of an IT and business framework for delivering great customer experiences.  Regarding the first, for some companies making large IT purchases, the way an enterprise employs CAPEX and OPEX accounting practices to categorize spending on technology may be a deal-breaker when coupled with the time and resources needed to implement and maintain a product. But these subjects are increasingly relegated to the 55-minute mark of conference calls that weigh the pros and cons of available technology. Because while few organizations make a platform purchase based solely on the cheapest price, astute IT buyers now discuss and invest in analytical, data-driven tools for sales, marketing and service, deployed across Web and mobile environments, that help produce differentiated customer experiences and strengthen personalized, real-time digital commerce offerings. That leads to the second key consideration: Improving the customer experience is the top driver for almost three-quarters (74%) of organizations participating in our next-generation customer engagement benchmark research.

One aspect of living in downtown Chicago is that there’s always something going on. But as distasteful as the subject matter of certain local events can be, some proceedings can inspire perspectives on a number of topics. One that occurs to me is how the retail industry can apply the new generation of mobile and location-based technologies not only to shape the customer experience but even rescue it from challenging situations. On Nov. 30, 2015, the Chicago Tribune reported that the Black Friday protests on the city’s Magnificent Mile cost local businesses 25 to 50 percent of their expected sales. While protestors have a constitutional right to free speech, business operators also had an opportunity and a responsibility – to proactively engage customers before, during and after the tumultuous Thanksgiving holiday weekend.

In our benchmark research into the next-generation contact center in the cloud more than two-thirds (69%) of organizations said they need to improve customer service, and market dynamics require them to do this is in new ways. Whereas today most (83%) compete on the services they offer, over the next two years 70 percent said they expect customer experience to be the top way they will compete, and nearly half (46%) said they expect to compete through self-service, digital channels. There is no doubt that consumers have changed the ways they prefer to communicate with each other and with companies. Mobile devices have become ubiquitous, and many consumers prefer to use chat-based technologies and mobile apps to engage. That is not to say that phone use is obsolete, as the research shows it and email are the most widely supported channels (each by 92% of companies), and while use of the corporate website (cited by 41%) is expected to show the greatest growth, more than one-fifth (22%) of participants said that the volume of inbound calls will show significant growth. Thus organizations must handle customer interactions across a variety of communication channels to maintain the business of all demographic groups.

Qlik helped pioneer the visual discovery market with its QlikView product. In some respects, Qlik and its competitors also spawned the self-service trend rippling through the analytics market today. Their aim was to enable business users to perform analytics for themselves rather than building a product with the perfect set of features for IT. After establishing success with end users the company began to address more of the concerns of IT, eventually creating a robust enterprise-grade analytics platform. This approach has worked for Qlik, driving growth that led to an initial
 public offering in 2010. The company now generates more than half a billion dollars in revenue annually, making it one of the largest independent analytics vendors. Of which based on their company and products was rated a Hot Vendor in our 2015 Value Index on Analytics and Business Intelligence and one of the highest ranked in usability.

NICE Systems was one of the first vendors I started to cover when I joined Ventana Research more than 11 years ago. Back then it was a pure-play vendor of workforce optimization (WFO) systems and was creating a portfolio of products by developing its own systems and acquiring niche vendors of call recording, quality management, workforce management, performance management and analytics. Over the years its portfolio has grown with new features, improved integration between the component parts, centralized administration and management capabilities, and a standard, modern user interface. The latest version of its core Workforce Optimization product was rated a Hot vendor in our 2015 WFO Value Index. It is still
undergoing development, and a new version is being marketed as Adaptive WFO as it uses analytics to become more information-driven.

Workiva offers Wdesk, a cloud-based productivity application for handling composite documents. I use the term “composite document” to refer to those in which text is created and edited collaboratively by multiple contributors and which incorporates tabular and numerical data from multiple sources in a controlled process. Composite documents often have formats defined by law, regulation or contract and must be created at periodic intervals. To comply with the requirement by the United States Securities and Exchange Commission (SEC) that companies “tag” their financial filings using eXtensible Business Reporting Language (XBRL), many companies acquired software to automate the creation and tagging of these composite documents.

Cloud-based computing has become widespread, particularly in line-of-business applications from vendors such as Salesforce and SuccessFactors. Our benchmark research also suggests a rise in the acceptance of cloud-based analytics.  We’ve seen the emergence and growth of cloud-only analytics vendors such as Domo and GoodData as well as cloud-based delivery by nearly all the on-premises analytics vendors. Almost half (48%) of organizations in our benchmark research on data and analytics in the cloud are using cloud-based analytics today, and two-thirds said they expect to be using cloud-based analytics within 12 months. In fact, only 1 percent said they do not intend to use cloud-based analytics at some point. This popularity leads to the question of how to maximize the value of investments in cloud-based analytics. We assert that one of the most important best practices for cloud-based analytics is to empower business users with modern analytics tools they can work with without relying on IT.

I have been involved in the contact center industry for more than 25 years and often see organizations that are slow in keeping up with consumers’ expectations; many of them seem reluctant to change, regardless of the need to do so. For example, agents of my cell phone operator ask the same four questions at the start of a call as they did 30 years ago; my bank supports several channels of communication, but it doesn’t provide the same information on all channels; and a well-known airline couldn’t tell me where my bag was for 36 hours (it was at the airport where I departed!). My list goes on, and I am sure you have your own.

For some people in sales and marketing who struggle to meet their quarterly targets, the blockbuster announcement that Microsoft will buy LinkedIn for US$26.2 billion may seem like a midyear holiday present: a digital business Rolodex filled with new global connections that can make the task of generating revenue dramatically easier. Problem is, sales leaders and revenue-focused marketers worth their weight already know everything there is to know about their target audience, and they’re taking action on that intelligence every day. They’re already power LinkedIn users who have optimized their personal profiles, ensured that their public-facing company information is up-to-the-minute, scrubbed buyer and influencer pages, read the latest corporate and competitive intel updates and scanned their Pulse newsfeeds, and they have done so for free before finishing their morning coffee ahead of the next meeting. Microsoft’s ownership of LinkedIn won’t cause top performers in sales and marketing to dramatically alter or change their productive and profitable habits. At least not right away.

I recently attended the Interactive Intelligence Interactions 2016 conference and came away with four key insights regarding the company’s plans and progress in providing contact centers in the cloud. These include the short-term success of PureCloud, the company’s financial performance, the importance of customer support and dealing with change.

If you’re a sales or marketing executive or manager, your window of business opportunity is closing rapidly. In fact it started closing the day you began your job. Time is not on your side – and your career may well hang in the balance. I want to help you shift that balance to your advantage.

It’s widely agreed that customer experience is now the most important dynamic for business. Any organization that wants to retain loyal and even vocal customers should do everything possible to ensure and maintain customer satisfaction. Software companies, especially those that promise to provide CRM and effective interactions across any channel at any time, should be good examples of embracing the methods they prescribe for using their products. But do they?

Organizations in all industries face various difficulties in managing product information. The most serious is providing complete, engaging information to consumers and customers on the internet. Newly developed products, mergers and acquisitions, changes to pricing and promotions in online commerce spur business growth, but these factors also increase the amount and complexity of product-related data and content. In addition the digital economy offers a new generation of services that are sold by subscription and packaged in various options and price points. As well, global diversification of suppliers, customers and business partners forces organizations to manage data quality and consistency in multiple locations, currencies and languages.

I have been meaning to write about Salesforce since its Dreamforce 2015 conference. Salesforce provides a platform, tools and applications for business and IT who claims to be the ‘no software’ company which as you will read is exactly what happened on May 10^th. Heck, Salesforce is making a lot of advances on its platform, its applications and even with Analytics and the Internet of Things. These changes are at the center of what at our analyst firm calls digital business innovation. Much of what it’s doing is very good, but now I am questioning whether the company’s foundation of business processes and technology platform has reached a point at which it can’t grow any further without impacting its own customers’ operations and success. That may be a harsh statement, but I think my reasoning will become clear as you read this perspective.

Organizations are facing a digital transformation, as I have written, that is rapidly changing the applications and services that businesses use to operate and deliver information. This new digital generation addresses the expectations of consumers and business partners for information and service in real time. One example of it is enterprise messaging. Recently I wrote about the shift to this technology and the challenges it poses for organizations that lack sufficient skills. However, new messaging appliances and virtualized messaging can carry some of this burden. By interconnecting them, organizations can be more confident in their ability to support the range of information and applications that operate in real time, not only for people but on devices and machines.

Enterprise messaging is the technology backbone of communications for applications and systems within and between organizations. Both its importance and its complexity are growing as organizations increasingly have to provide real-time responses to business customers and consumers as well as their own business professionals who support them and their internal supply chains. The variety of use cases for enterprise messaging also is growing rapidly, expanding to the Internet of Things (IoT) market of sensors and devices including wearable technology; to new generations of applications and services for consumers and customers; to cloud computing and the shift to platform or infrastructure as a service (PaaS or IaaS); and to real-time big data and analytics. All of these innovations will enable these types of transformation to digital business that is impacting organizations around the world.

The learning management system (LMS) offers opportunity for organizations to progressively enhance the effectiveness of their workforce. An advanced LMS can be more than a digital version of an organization’s training programs for specific jobs or to achieve compliance with policies and regulations. It can provide dynamic yet informal learning that business units can create, deploy and sustain through their own efforts. Last year I outlined the benefits of this new generation of learning management systems.

I hope this title captures your attention; I’m trying to make a point about the chaos going on in managing and operating marketing. What marketing needs in 2016 is to manage and optimize its efforts in a more unified manner. This perspective kicks off a new series on the challenges for marketing to automate or execute tasks and manage toward maximum performance. We all know that the craft of marketing is in need of significant transformation, from the CMO throughout the entire marketing organization and all the way out to the experience of consumers and customers. But this may be a fanciful mission, as applications and technology does not really automate marketing let alone manage it. Most marketing automation products are specialized applications that are not used by marketing management, let alone front-line marketing managers; they are for specialized needs in demand generation or digital marketing that personalizes inbound and outbound interactions with contacts for the purpose of advancing dialogue and creating relationships. Marketing automation, like its cousin sales force automation, has been a placeholder category that describes only a narrow slice of marketing, and the term has been co-opted by the industry for its own purposes. Though some observers predict that CMOs will outspend CIOs and other leaders of the business in technology investments, I have debunked this ludicrous idea; even if it were true, that would not make marketing departments much more efficient in their management and operations. To counterbalance the silliness of the marketing automation dialogue, I plan to bring you a series on key areas for investment to start the conversation. Evaluating them should help Marketing demonstrate its commitment to promoting effectively its organization and its products and services. Here is an overview of the many issues in the landscape.

For several years I have been advocating that sales organizations adapt their processes and applications to optimize both sales performance and the customer experience. For details see my research agenda for last year. However, it appears that not many sales organizations have responded to this challenge; many can barely maintain their quarterly sales forecasts and monthly pipeline, track progress toward quotas and ensure that sales commissions are processed promptly and paid accurately. A great many are still using spreadsheets for these critical activities. Yet our benchmark research finds that more than half (61%) who use them for commissions said this makes the effort more difficult. Elsewhere, I have seen B2B sales organizations continue down the old path of annoying prospects with direct cold calling and email instead of nurturing real relationships. For B2C sales, the digital age of search engine optimization (SEO) and pay-per-click (PPC) has begun to haunt prospects by inserting ads in our personal social media channels. My research suggests that these practices are not due to bad intentions but to force of habit and lack of desire, time and resources to develop a modern strategy and plan. Most are just managing the basics of their sales processes and relying on sales force automation (SFA) systems, reporting and dashboards, which will only produce more of the same, less than optimal results.

Verint is an established vendor of workforce optimization, advanced analytics and self-service products for customer experience management. Recently it announced its acquisition of Contact Solutions, whose products complement Verint’s. The acquisition adds analytics capabilities and fraud detection software, both of Verint will incorporate into its existing products. Contact Solutions also brings to the merger IVR and My:Time, two innovative products that add to Verint’s portfolio for customer self-service.