Vena Solutions offers midsize organizations a platform for financial planning, analysis and reporting as well as software to manage accounting consolidation and close processes. From the start, Vena has designed its applications to meet the needs of midsize organizations, which typically have the same requirements as large enterprises but with significantly fewer resources to acquire, manage and maintain technology. Ventana Research named Vena a Value Index Leader in Adaptability and a Vendor of Merit in its 2022 Value Index on Business Planning.
In today’s data-driven world, organizations need real-time access to up-to-date, high-quality data and analysis to keep pace with changing market dynamics and make better strategic decisions. By mining meaningful insights from enterprise data quickly, they gain a competitive advantage in the market. Yet, organizations face a multitude of challenges when transitioning into an analytics-driven enterprise. Our Analytics and Data Benchmark Research shows that more than one-quarter of organizations find it challenging to access data sources and integrate data and analytics in business processes. Vendors such as IBM offer a broad set of analytics tools with self-service capabilities that allows organizations to reduce IT dependencies and enables decision-makers to recognize performance gaps, market trends and new revenue opportunities. Its technology can simplify data access for self-service applications, enabling users to make business decisions informed by insights and take the guesswork out of decision-making.
The theme of this year’s Oracle NetSuite SuiteWorld was “Full Suite Ahead,” with content aimed at demonstrating to customers (and prospective buyers) the value of using more of what NetSuite has to offer. The business logic behind this concept goes beyond the obvious objective of upselling existing customers to increase the average annual recurring revenue. As is often the case with subscription businesses, customers fail to take advantage of what’s already included in their service. Ensuring that customers are achieving full value is essential to retaining them, and almost always a precondition to selling them more. For a cloud software vendor, this translates to having an effective customer success organization backed by a customer-centric product strategy and a product management organization that delivers on the strategy. All of this was on display at the event.
The pandemic years saw an exponential rise in organizational investment in digital learning, and for good reason. With in-person learning no longer an option, organizations were forced to quickly adapt to the changing world of work in order to ensure workers were prepared with the knowledge and training necessary to operate in ways they had never before seen. Beyond operational imperatives, organizations have turned to digital learning systems to find new ways to track and bolster productivity, sentiment and engagement of the workforce. This serves to protect the investments made in hiring, onboarding and upskilling or reskilling talent by mitigating risk and regrettable attrition as well as helping employees along a career path that is achievable and desirable for the employee and strategically advantageous to the employer.
Almost all organizations are investing in data science, or planning to, as they seek to encourage experimentation and exploration to identify new business challenges and opportunities as part of the drive toward creating a more data-driven culture. My colleague, David Menninger, has written about how organizations using artificial intelligence and machine learning (AI/ML) report gaining competitive advantage, improving customer experiences, responding faster to opportunities and threats, and improving the bottom line with increased sales and lower costs. One-quarter of participants (25%) in Ventana Research’s Analytics and Data Benchmark Research are already using AI/ML, while more than one-third (34%) plan to do so in the next year, and more than one-quarter (28%) plan to do so eventually. As organizations adopt data science and expand their analytics initiatives, they face no shortage of options for AI/ML capabilities. Understanding which is the most appropriate approach to take could be the difference between success and failure. The cloud providers all offer services, including general-purpose ML environments, as well as dedicated services for specific use cases, such as image detection or language translation. Software vendors also provide a range of products, both on-premises and in the cloud, including general-purpose ML platforms and specialist applications. Meanwhile, analytic data platform providers are increasingly adding ML capabilities to their offerings to provide additional value to customers and differentiate themselves from their competitors. There is no simple answer as to which is the best approach, but it is worth weighing the relative benefits and challenges. Looking at the options from the perspective of our analytic data platform expertise, the key choice is between AI/ML capabilities provided on a standalone basis or integrated into a larger data platform.
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.
The starting point of an era is never precise and rarely conforms to neat calendar delineations. For example, the start of the 20th century is associated with the outbreak of war in 1914. So I expect that decades from now, the consensus will hold that what became known as the 21st century began in the year 2020, with the pandemic serving as a catalyst that accelerated already existing trends and forced changes to prevailing norms and practices. This and other disruptive events that have followed are reverberating through economic and social networks and will ultimately result in some new equilibrium, but the ructions on the way there will be sharp and ever-present. Large-scale disruptions in most aspects of doing business have forced change on organizations. In this climate, the financial planning and analysis group can play a far more important role by using technology to enhance organizational agility and improve performance.
IBM Planning Analytics with Watson is a comprehensive, cloud-based business planning application that supports what Ventana Research calls integrated business planning. We coined this term in 2007 to describe a high-participation approach to business planning that integrates strategy, operations and finance. Our Next Generation Business Planning Benchmark Research demonstrated the value of IBP: Organizations that link planning processes get better results. Sixty-six percent of organizations that have an integrated method say it works well or very well, compared to only 25% that have little or no connection between plans.
Topics: Predictive Analytics, Office of Finance, embedded analytics, Business Intelligence, Business Planning, Financial Performance Management, Watson, Digital transformation, AI and Machine Learning, digital finance, profitability management
The idea of partnerships in business is most definitely not new. Wholesaling through distributors and retailers is centuries old. For some industries, their entire model is selling and servicing through partners. Think auto parts, and the auto part stores visible in most neighborhoods. But what is new is that partnerships are moving beyond this reseller model towards product partnerships, where a seller’s products and services are supplemented by other vendors’ offerings from adjacent and complementary markets.
It has been three years since Oracle hosted a CloudWorld event live in Las Vegas, and it is clear the time has not been wasted. With 12 new releases since the last event, the Oracle human capital management product team has made significant advances in both product and service. Three areas of note: Oracle HCM’s continued focus on personalization of experience, meeting the HCM needs of the healthcare industry and advancing the Oracle Cloud Recruiting offering.
Topics: Human Capital Management
If you’ve ever been to London, you are probably familiar with the announcements on the London Underground to “mind the gap” between the trains and the platform. I suggest we also need to mind the gap between data and analytics. These worlds are often disconnected in organizations and, as a result, it limits their effectiveness and agility.
I have previously written about growing interest in the data lakehouse as one of the design patterns for delivering hydroanalytics analysis of data in a data lake. Many organizations have invested in data lakes as a relatively inexpensive way of storing large volumes of data from multiple enterprise applications and workloads, especially semi- and unstructured data that is unsuitable for storing and processing in a data warehouse. However, early data lake projects lacked structured data management and processing functionality to support multiple business intelligence efforts as well as data science and even operational applications.
The door opened to a new world in 2020, one that renders old assumptions suspect and future outcomes more varied and uncertain. It’s likely that the transition to what’s next will be bumpy, which makes planning more effectively that much more strategic.
Prophix offers cloud financial software for planning, budgeting, reporting and statutory financial consolidation designed to meet the requirements of midsize organizations and divisions of larger corporations. The company was one of the first to offer a planning platform capable of bringing together a company’s diverse planning processes and financial planning and budgeting. Its consolidation and close automation enable a shorter close and improved accounting staff productivity for midsize corporations that have even moderately complex legal entity structures that operate in multiple currencies. Increasingly, organizations are finding that having the right finance and accounting department software tools helps attract and retain the best talent.
For quite a few years now, two trends have put the contact center on a collision course. First, the technology used to handle customer inquiries has been evolving quickly, moving organizations farther and farther away from the traditional mode of primarily answering voice calls. At the same time, consumers have become much more demanding. There’s no doubt that customers are more likely to use quality of service as a gauge for whether they should continue doing business with an organization. They’re more willing to bolt for a competitor if they have a bad experience. In short, they want more of everything, and contact centers have been trying to accommodate these expectations.
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.
The worldwide market for software to manage indirect income taxes, which includes sales and use, goods and services (GST) and value-added taxes (VAT), has been growing because of recent compliance mandates, the growth of e-commerce as well as a desire to accelerate business processes by reducing friction in areas such as tax compliance, cutting administration costs and lowering risk. Vertex provides businesses with cloud-based software that manages indirect tax processes for midsize and larger companies, especially for those with complex tax profiles. Vertex enables local and worldwide compliance backed by its ongoing tax research that continually compiles tax rules for over 19,000 jurisdictions. Because links with core financials is an essential capability for organizations of any size, Vertex maintains pre-built integrations with the leading ERP and financial management systems. Cloud-based systems are now the norm to support teams that are geographically dispersed and enable hybrid work environments. Ventana Research asserts that by 2026, a majority of midsize and larger companies will have digitized their indirect tax compliance to ensure accuracy as jurisdictions step up audits to increase revenues.
ERP systems have been a fixture of organizational process management and record keeping for so long (more than three decades) that it is likely that few who use the software are aware that ERP is an acronym for Enterprise Resources Planning. Its smooth and uninterrupted functioning is essential to an organization’s accounting and finance processes. In manufacturing and distribution, ERP manages inventory and logistics. Some organizations use it to handle human resources functions like tracking workers, payroll and related costs. Its initial introduction represented a major advance, but its subsequent evolution has been slow and mainly a series of incremental refinements.
Pressures to engage consumers through every interaction and provide a delightful customer experience are influencing advancements in business and technology. Organizations are challenged to manage friction points experienced by billions of consumers amid expanding digital channels. These issues must be addressed to engage and respond to customers every second of the day.
Traditional key performance indicators used for performance measurement in contact centers are no longer sufficient. These outdated standards don’t reliably inform mid- and upper-level leadership about the true impact of agent work and behavior. Organizations should begin to expand the notion of what’s important in order to make the contact center a stronger organizational institution, more closely tied to others who impact the customer experience. Outside the contact center, people are keen to understand the relationship between what’s being spent and what’s coming in: revenue and growth.
Some weeks back I published my thoughts about the traditional applicant tracking system and how that technology is no longer sufficient to support organizations’ complex recruiting needs. This is particularly true when trying to take a one-size-fits-all approach to hiring processes. Having identical hiring processes and requirements for professional hires as for low-complexity, low barrier-to-entry roles will inevitably result in lost candidates, frustrated recruiters and hiring managers, and low application-to-hire conversion rates. It doesn’t have to be that way. The right technology can support a hiring process that is purpose built for the segment it is intended to attract and hire.
In their pursuit to be data-driven, organizations are collecting and managing more data than ever before as they attempt to gain competitive advantage and respond faster to worker and customer demands for more innovative, data-rich applications and personalized experiences. As data is increasingly spread across multiple data centers, clouds and regions, organizations need to manage data on multiple systems in different locations and bring it together for analysis. As the data volumes increase and more data sources and data types are introduced in the organization, it creates challenges to storing, managing, connecting and analyzing the huge set of information that is spread across multiple locations. Having a strong foundation and scalable data management architecture in place can help alleviate many of the challenges organizations face when they are scaling and adding more infrastructure. We have written about the potential for hybrid and multi-cloud platforms to safeguard data across heterogenous environments, which plays to the strengths of companies, such as Actian, that provide a single environment with the ability to integrate, manage and process data across multiple locations.