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Finance departments don’t immediately come to mind in conversations about social collaboration technology. Most of the software used for social collaboration that I’ve seen demonstrated focuses on the
sales process or for broader employee engagement. The Facebook-style interface may cause finance department managers and executives to roll their eyes, especially if they’re over 40 years old. Yet business and social collaboration is an important set of capabilities that has been taking hold in business. Our benchmark research shows it ranking second behind analytics as a technology innovation priority. It will gain adoption over the next several years as software transitions from the rigid constructs established in the client/server days, which force users to adapt to the limitations of the software, to fluid and dynamic designs that mold themselves around the needs of the user. Perhaps because most of the attention so far on the benefits of collaboration has focused on front-office roles, there’s less awareness of the potential in back-office and administrative functions. Indeed, the same research reveals that those in front-office roles five times more often than those in accounting and finance roles (21% vs. a mere 4%) said that business and social collaboration are very important to their organization. However, I assert it’s just a matter of time before the finance group understands that social collaboration has substantial potential to improve its performance.
In examining why this change will occur, let’s start with some background. “Doing business” is all about collaboration, on which my colleague Mark Smith commented in an earlier perspective. Before communication technologies began to eliminate the constraints of time and space, people relied mainly face-to-face collaboration. (Postal letters were another option but they were very slow and limited interaction.) Voice mail was the first breakthrough in enabling people to collaborate quickly across time and space. Busy individuals could conduct conversations through a series of voice messages, discussing an issue in some depth and agreeing on an approach without speaking in real time. Much of business investment in information technology over the past two decades has been aimed at enabling good communications among different elements located in separate buildings, cities and even countries. The same is true for finance.
We all know that the eruption of social media – in both group settings like Facebook and one-to-many channels such as Twitter – has changed the dynamics of how people – especially those under the age of 40 – communicate. A couple of years ago, a group of teenage girls became trapped in a sewer under Adelaide, Australia. It took several hours to rescue them because the one with a phone used it to post their plight on her Facebook page rather than call someone. This example may be extreme, but it illustrates intergenerational differences in expectations of how one communicates. As with IM, software companies that build business applications are beginning to include Facebook- and Twitter-like capabilities to support collaboration. Examples include application platforms such as Salesforce.com’s Chatter, IBM’s Connections and stand-alone software that can be integrated with another vendor’s offering such as Socialtext that is now owned by Peoplefluent. Software that fosters collaboration can improve efficiency, for example, by resolving issues faster or finding easier or less expensive alternatives to addressing a need. It can improve effectiveness by improving customer satisfaction or enabling more informed decisions sooner. It can foster better alignment across business units as well across and within departments by enabling closer communications among their people.
Social collaboration is off to an encouraging start, but it’s easy to see where improvements are needed, especially to be useful to the finance function. Ideally, collaboration software will be able to understand the context of the work at hand, the role of the individual participant and the relationships the individual has with others in that context. A technology like Google Glass has the potential to enable a manager, while reviewing a report, to see that there have been comments posted related to specific numbers, text or charts and then select and read these just by moving his or her eyes.
As well, software imbued with social collaboration capabilities should understand and automatically manage the various types of relationships among individuals. For example, people in a company typically have a general role (“I’m in Finance”) and one or more task-specific ones (“I’m the director of financial planning and analysis”). Some relationships are persistent while others begin and end with a project. Issues that arise may be open to all or confined to specific groups, subsets of groups or a private dialogue. Queries or comments may be general, specific or somewhere in between. Some conversations, especially in finance and tax departments, must be tightly controlled. Software that understands the context of the work performed and automates the process of managing the who, what and when of the communications will support more effective collaboration, faster completion of tasks, greater situational awareness with the organization and as a result better decision-making.
Which brings me back to the relevance of social collaboration for finance professionals. There are many use cases for comprehensive collaboration capabilities in ERP or accounting and financial performance management software. A good deal (maybe too much) of what goes on operationally in finance departments involves checking details and correcting errors – activities that require direct communications. Resolving billing issues could be streamlined if receivables and sales or payables and purchasing were connected to the appropriate collaborative network in the context of executing business processes. For example, end-of-period reconciliations could proceed faster if communications among the right people in the departments involved less effort. The financial close has multiple steps where time saved by resolving snags or clearing up ambiguities consistently can have a meaningful impact on shortening the process. Likewise, planning and review involve a great deal of collaboration, especially in understanding assumptions and expectations or providing perspectives on causal factors behind better or worse than expected results.
Unlike those in sales and marketing, the stereotypical accountant and finance specialist is not thought of as “social.” And at the moment, few people working in finance departments say that social collaboration capabilities are very important to their jobs. An important aspect of my research agenda for this year points to the need to address the demographic shift from executives and managers from the baby-boom generation to those who grew up with computer technology. These shifts will drive demand for a new generation of software, one that emphasizes IT-enabled collaboration, mobility and agility. Social collaboration used in business applications should be more than a Facebook metaphor. It addresses a key drawback of instant messaging systems: the fact that in business, individuals have multiple roles and multiple networks of people with whom they interact. When tightly integrated into business software of all kinds, social collaboration will become an essential capability by enabling people to resolve issues faster and with less effort than other means of communication. Vendors that focus on the finance function should ignore today’s lack of enthusiasm for social but more practical collaborative capabilities and ensure that their software is designed for the next generation of financial software users.
Regards,
Robert Kugel – SVP Research
Information technology for business is changing rapidly as organizations demand innovation to help them discover insights and facts. Our research into business technology innovation found analytics to be the 
top priority in 39 percent of organizations. Businesses feel pressure to be better, faster and smarter in operating processes, and understanding their various types of information is a key to success. Businesses are looking to capture value from all types of information both within the enterprise and on the Internet. In this context technology providers are now using the term “discovery” to capture potential buyers’ attention; it became an area for technology spending in 2012 and likely will be for years to come. In fact my colleague Tony Cosentino has identified discovery as one of the four pillars of big data analytics.
Discovery is one of many business analytics methods that can be used realize value from current and future investments into big data. Discovery, of course is the act of finding something, whether it’s truly new or just overlooked. Wikipedia adds, “With reference to science and academic disciplines, discovery is the observation of new phenomena, new actions or new events and providing new reasoning to explain the knowledge gathered through such observations with previously acquired knowledge from abstract thought and everyday experiences. Visual discoveries are often called sightings.”
In business the knowledge gathered by individuals engaged in discovery is critical to provide context; typically those people are analysts responsible for the organization’s analytics or increasingly are business professionals competent to delve into the discovery process; for either, analytic technology should provide meaningful information in dynamic fashion. Done right, discovery produces intelligence, and analytic tools have improved the usability that enables more people to discover insights using this class of technology. I have already pointed out why conventional business intelligence is failing business; improving on these failings should also be a guide to what we need from discovery technology. With the wide adoption of big data technologies in varying approaches, organizations need to find the right tools to take advantage of it, but adequate data and visual discovery are not currently available in almost one-fifth (19%) of organizations participating in our technology innovation research.
There are four main types of discovery for business analytics: in no particular order, they are event, data, information and visual. Let’s consider each of them and the potential they hold for realizing full value from business analytics and big data investments.
Event Discovery: Enterprise networks now must handle extreme velocity in the streams of events that pass into and through them. If they are processed effectively, discovery through analytics could reveal current bottlenecks and opportunities for improvement or if trended and projected could indicate patterns developing in a negative direction. Processing events in a real-time or right-time manner has evolved from complex event processing into a category of its own, operational intelligence. Our research in this area found that nearly half (45%) organizations consider it very important to analyze business and IT events, and another 44% indicated it is somewhat important. The process of discovery applied to events can take many directions; for example, discovery analytics can immediately notify someone to take action, or the results can be displayed visually to make it easier to identify outliers or trends that should be further analyzed for review. As well, discovering relationships between events is very important to 53 percent of organizations. But the right tools are necessary for success. Our research shows that the large majority (91%) of organizations that use specialized tools for this are satisfied with them, compared to 76 percent that use general-purpose BI tools. The role of event discovery, now being called big data in motion, is changing rapidly as Tony Cosentino has pointed out.
Data Discovery: Enterprise databases contain ever larger volumes of structured data that describe transactions and interactions with their customers, their products and employees, the locations where their business operates and relations with their partners and suppliers. This kind of data is significant and can be sourced from in-house business applications and data warehouses and from software rented in the cloud computing environments, as well as through new investments in big data. From whatever source, having more interactive and data-centric discovery is critical to empower analysts and even data scientists. Data discovery is not new, but it has evolved greatly. Intuitive and flexible a new tools have advanced from the foundation of OLAP to perform data discovery on large volumes of source data and place it into a business model or analyze it while still in its almost original formats. The ability to combine and relate data from Internet sources expands the realm of what is possible to know and act on while expending less time and resources. Many business intelligence suppliers are just beginning to see what is required to meet the needs of today’s analysts compared to the past needs of IT or BI professionals needs to publish reports and dashboards. Our research finds that exploring data underlying analytics in a discovery manner is a critical business analytics need in 37 percent of organizations. Some new big data-oriented analytic tools can do more comprehensive data discovery, and IT departments will have accommodate them to provide what analysts need to do their jobs.
Information Discovery: Organizations now must handle a broader variety of information than ever before, including documents and semi-structured content whose data is not contained in a database. This wealth of information provides an opportunity to increase business understanding, but users need to access and integrate it for a range of tasks such as fraud, risk and compliance; process improvement; and reporting and analytics. This information can also be combined with data from databases to provide a comprehensive foundation for applying discovery processes. Our research shows that content is the second-most important type of data in 59 percent of organizations, right after customer data (71%). We believe that information optimization is a key benefit of big data and information management investments, but as I have pointed out it requires flexible technology to utilize all this information. Information discovery was once left to very expensive technology and specialized resources, and hence was beyond the reach of many organizations. Now many vendors offer tools that can perform content analytics to discover key information in proprietary formats and harvest it for business operations. The new generation of tools also provides the ability to define templates and placement for information to be integrated without the work of developers; it can analyze the layouts of documents and process their contents on an automated basis.
Visual Discovery: This is the latest technology craze as analysts clamor to add it to their analytic tool sets. Our research finds that presenting data visually is the second-most demanded critical business analytics capability for 48 percent of organizations. This type of discovery helps visualize large volumes of data to add new focus to finding areas of opportunity and challenges. Visualization may seem deceptively easy, but it is actually quite difficult to design technology that a range of nontechnical roles find easy to understand and present. I have seen vendors just attempt to lay more sophisticated visualization on top of their existing products, but doing this does not produce the usability and interactivity users insist on; lacking these qualities has severely hindered adoption. Being able to use visualization as a selection method for further discovery dramatically reduces the time it takes users to analyze data and find new insights. At some point in the visual discovery process, users want to share a visualization or a chart for further collaboration, to identify potential places for root-cause analysis or to make recommendations for resolution. At this point in development, however, most of the technology in visual discovery is not able to easily associate comments or bullets to a specific view and then enable sharing or collaboration on it electronically.
Not all discovery technology is created equal, as my discussion of the four big types of discovery shows. Some tool providers excel at one type, but few do all of them well. Thus your organization will have to create a discovery strategy as part of your business analytics efforts and choose and budget appropriately as you identify your most critical needs. You certainly will need to do something: Our business analytics research finds that analysts in 42 percent of organizations spend the majority of their time on data-related activities instead of actual analysis, so it is vital to reduce these chores and that ensure discovery methods do not increase that time; have IT staff automate these tasks through data integration and virtualization. For the CIO, it is important to ensure you are not just investing into evolution of your business intelligence tools as Tony points out; remember that the priority now is meeting the needs of the business and especially the analysts who are held responsible for analytics. Just serving reports and dashboards faster and in prettier form in many cases is not going to provide the critical insights. As I have already pointed out, putting more charts in dashboards or embedding key performance indicators are not smart strategies for guiding business improvement.
There is work to do here in convincing skeptics of the need for investment.
According to our business technology innovation research building the business case (43%) is the second-greatest t barrier to adopting innovative technology like discovery, following lack of resources (51%). It is not easy to use a traditional business case that projects value and benefits from a specific investment in the case of discovery, where the technology is about finding the unknown and providing benefits depends on the competency and skill of your analysts and business professionals as well as the effectiveness of the technology. Because usability is critical (the evaluation category criteria most often classified as important by 64% of organizations in our research) you must look beyond just the capabilities in the technology to how easily a variety of roles can use it and collaborate on the insights found from it. Most tools are only suitable for certain roles and maybe not for every analyst, let alone directors or vice presidents. These innovations by many technology vendors are just coming to market. Many organizations decide the potential value of an investment on the time to utilization of the tool and the projected time to value on potential insights from it; for analytics through discovery that is not always easy today.
To evaluate the benefits of the new generation of business analytics that utilize the discovery methods discussed here, start with a conversation internally to identify your needs and look at some online demos to see what is possible. Our next-generation business intelligence research finds discovery to be a critical consideration for 69 percent of organizations, which indicates the strong interest in discovery technology that will work for business and IT. From another perspective, our spreadsheets in the enterprise research finds that 74 percent of organizations are still using personal spreadsheets with BI to meet many of their data and visual discovery needs, at the same time as 56 percent find it time-consuming to combine spreadsheets through copying and pasting and more than one-third (35%) find data errors from their use of spreadsheets. As my colleague Robert Kugel puts it, it is time to end denial about the use of spreadsheets and focus on buying tools designed for complex tasks like discovery. For IT organizations, it is essential to address data and integration needs for analytics and analysts so business is not spending so much time on data-related tasks; they also should understand that while there will be more tools and vendors in use, the architecture and support of them should be simplified. For business, it is critical to understand what the types of discovery are all about and where technology innovation in 2013 can help make your organization’s processes run better and faster. It will be well worth your time to investigate why more organizations – and maybe your competitors among them – are getting benefits from making their business to smarter by using discovery.
Regards,
Mark Smith
CEO & Chief Research Officer
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