Microsoft has been steadily pouring money into big data and business intelligence. The company of course owns the most widely used analytical tool in the world, Microsoft Excel, which our benchmark research into Spreadsheets in the Enterprise shows is not going away soon. User resistance (cited by 56% of participants) and lack of a business case (50%) are the most common reasons that spreadsheets are not being replaced in the enterprise.  The challenge is ensuring the spreadsheets are not just personally used but connected and secured into the enterprise for a range of consistency and potential errors that all add up to more work and maintenance as my colleague has pointed out recently.

Along with Microsoft SQL and SharePoint, Excel is at the heart of the company’s BI strategy. In particular, PowerPivot, originally introduced as an add-on for Excel 2010 and built into Excel 2013, is a discovery tool that enables exploratory analytics and data mashups. PowerPivot uses an in-memory, column store approach similar to other tools in the market. Its ability to access multiple data sources including from third parties and government through Microsoft’s Azure Marketplace, enables a robust analytical experience.

Ultimately, information sources are more important than the tool sets used on them. With the Azure Marketplace and access to other new data sources such as Hadoop through partnership with Hortonworks as my colleague assessed, Microsoft is advancing in the big data space. Microsoft has partnered with Hortonworks to bring Hadoop data into the fold through HDInsights, which enable familiar Excel environments to access HDFS via HCatalog. This approach is similar to access methods utilized by other companies, including Teradata which I wrote about last week. Microsoft stresses the 100 percent open source nature of the Hortonworks approach as a standard alternative to the multiple, more proprietary Hadoop distributions occurring throughout the industry. An important benefit for enterprises with Microsoft deployments is that Microsoft Active Directory adds security to HDInsights.

As my colleague Mark Smith recently pointed out about data discovery methods, the analytic discovery category is broad and includes visualization approaches. On the visualization side, Microsoft markets PowerView, also part of Excel 2013, which provides visual analytics and navigation on top of the Microsoft’s BI semantic model. Users also can annotate and highlight content and then embed it directly into PowerPoint presentations. This direct export feature is valuable because PowerPoint is still a critical communication vehicle in many organizations. Another visual tool, currently in preview, is the Excel add-in GeoFlow, which uses Bing Maps to render visually impressive temporal and geographic data in three dimensions. Such a 3-D visualization technique could be useful in many industries.  Our research into next generation business intelligence found that deploying geographic maps (47%) and visualizing metrics on them (41%) are becoming increasing important but Microsoft will need to further exploit location-based analytics and the need for interactivity.

Microsoft has a core advantage in being able to link its front-office tools such as Excel with its back-end systems such as SQL Server 2012 and SharePoint. In particular, having the ability to leverage a common semantic model through Microsoft Analytical Services, in what Microsoft calls its Business Intelligence Semantic Model, users can set up a dynamic exploratory environment through Excel. Once users or analysts have developed a BI work product, they can publish the work product such as a report directly or through SharePoint. This integration enables business users to share data models and solutions and manage them in common, which applies to security controls as well as giving visibility into usage statistics to see when particular applications are gaining traction with organizational users.

Usability, which our benchmark research into next-generation business intelligence identifies as the number-one evaluation criterion in nearly two-thirds (64%) of organizations, is still a challenge for Microsoft. Excel power users will appreciate the solid capabilities of PowerPivot, but more casual users of Excel – the majority of business people – do not understand how to build pivot tables or formulas. Our research shows that only 11 percent of Excel users are power users and most skill levels are simply adequate (49%) compared to above average or excellent. While PowerView does give some added capability, a number of other vendors of visual discovery products like Tableau have focused on user experience from the ground up, so it is clear that Microsoft needs to address this shortcoming in its design environment.

When we consider more advanced analytic strategies and inclusion of advanced algorithms, Microsoft’s direction is not clear. Its Data Analysis eXpressions (DAX) can help create custom measures and calculated fields, but it is a scripting language akin to MDX. This is useful for IT professionals who are familiar with such tools, but here also business-oriented users will be challenged in using it effectively.

A wild card in Microsoft’s BI and analytics strategy is with mobile technology. Currently, Microsoft is pursuing a build-once, deploy-anywhere model based on HTML5, and is a key member of the Worldwide Web Consortium (W3C) that is defining the standard. The HTML5 standard, which has just passed a big hurdle in terms of candidate recommendation is beginning to show value in the design of new applications that can be access through web-browsers on smartphones and tablets. However, the success or failure of its Windows 8-based Surface tablet will be the real barometer since its integration with the Office franchise is a key differentiator. This approach of HTML5 could be challenging as our technology innovation research into mobile technology finds more organizations (39%) prefer native mobile applications from the vendors specific application stores compared to 33 percent through web-browser based method and a fifth with no preference. Early adoption of the tablet has not been strong, but Microsoft is said to be doubling down with a new version to be announced shortly. Success would put Office into the hands of the mobile workforce on a widespread basis via Microsoft devices, which could have far-reaching impacts for the mobile BI market.

As it stands now, however, Microsoft faces an uphill battle in establishing its mobile platform in a market dominated by Android and Apple iOS devices like the iPhone and iPad. If the Surface ultimately fails, Microsoft will likely have to open up Office to run on Android and iOS or risk losing its dominant position.  My colleague is quite pessimistic about Microsoft overall mobile technology efforts and its ability to overcome the reality of the existing market. Our technology innovation research into mobile technology finds that over half of organizations have a preference for their smartphone and tablet technology platform, and the first ranked smartphone priorities has Apple (50%), Android (27%) and RIM (17%) as top smartphone platforms with Microsoft a distant fourth (5%); for tablets is Apple (66%), Android (19%) and then Microsoft (8%). Based on these finding, Microsoft faces challenges on both the platform front and if they adapt their technology to support others that are more preferred and used in business today.

Ultimately, Microsoft is trying to pull together different initiatives across multiple internal business units that are known for being very siloed and not organized well for customers.  Ultimately, Microsoft has relied on its channel partners and customers to figure out how to not just make them work together but also think about what is possible since they are not always given clear guidance from Redmond. Recent efforts find that Microsoft is trying to come together to address the big data and business analytics challenge and the massive opportunity it represents. One area in which this is coming together is Microsoft’s cloud initiatives. Last year’s announcements of Azure virtual machines enables an infrastructure-as-a-service (IaaS) play for Microsoft and positions Windows Azure SQL Database as a service. This could make the back end systems I’ve discussed available through a cloud-based. Ironically, the cloud-based Office365 suite does not include core productivity applications such as Excel and PowerPoint, so front-end access will still come through the client version of the software.

For organizations that already have installed Microsoft as their primary BI platform and are looking for tight integration with an Excel-based discovery environment, the decision to move forward is relatively simple. The trade-off is that this package is still a bit IT-centric and may not attract as many in the larger body of business users as a more user-friendly discovery product might do and address the failings of business intelligence. Furthermore, since Microsoft is not as engaged in direct support and service as other players in this market, it will need to move the traditionally technology focused channel to help their customers become more business savvy. For marketing and other business departments, especially in high-velocity industries where usability and time-to-value is at a premium and back-end integration is secondary, other tools will be worth a look. Microsoft has great potential and with analytics being the top ranked technology innovation priority among its customers I hope that the many divisions inside the global software giant can finally come together to deliver a comprehensive approach.

Regards,

Tony Cosentino

VP and Research Director

When it comes to today’s customers, companies have to be smart if they are going to anticipate and meet new customer expectations. These days IBM talks about doing most things in “smart” ways. Recently I was briefed on IBM’s Smart Customer Analytics, but it took me quite a while to find information about it on the company’s not-so-smart website. Surprisingly since business analytics is so important to IBM current and ongoing investments and is the top ranked technology innovation priority in 39 percent of organizations according to our benchmark research.

IBM’s recent history in analytics began with its acquisition of Cognos, and it has gone on acquiring analytics vendors, including SPSS, Unica, Tealeaf and many others. Through these purchases IBM has assembled a comprehensive set of capabilities to support the complete customer life cycle, which it defines as acquire, grow and retain. At the acquire stage the products support granularity of  customer segmentation, which smart companies can use to ensure that customers receive the right messages through the channel of their choice. To grow the customer base it supports analysis of customer issues, sentiment and trends to support cross- and up-selling, and the collection of all customer data to create a 360-degree view of the customer. To support customer retention IBM offers predictive analysis to identify customers at risk of defection and suggest actions to address issues, as well as to generate insights to define and execute an ongoing customer engagement strategy.

How does IBM support all these activities? The answer starts with data, which is at the heart of customer analytics. IBM segments it into descriptive data (such as name, address and other attributes), behavioral data (transactions such as orders and payments), interaction data (including email messages, chat scripts, Web streams and CRM notes) and attitudinal data (such as customer feedback, market research and social media comments). Eventually companies need to bring together, rationalize and analyze all customer data, from any source, type (structured, unstructured and event-based) or time frame; the more they include, the fuller their customer view will be. Customer analytics has tools that extract data from multiple data sources, an information management platform that brings the data, predominantly structured data, text and social media, together, and makes it available for the analytics platform. These requirements and steps for customer analytics requires integrating all of this information requires big data technology that IBM has advanced as my colleague notes but will need to be further integrated into its existing customer focused efforts and further embrace its current big data analytics that we have assessed.  This includes tools that support data and text mining, business rules management, entity analytics, sentiment analysis and business intelligence; together they help companies carry out predictive modeling, sentiment analysis, forecasting and simulation, social analytics, and customer feedback analysis. The results are shown in scorecards, dashboards and reports that support the latest visualization techniques, and which support real-time decision-making.

Through the process of acquiring technology vendors to support business analytics, enhancing their products, developing new capabilities and integrating the products, IBM has created an impressive set of capabilities. However, it is missing speech analytics, which my research into customer analytics shows can be a prime source of customer insights. These days most companies have at least one contact center, and almost all centers record some if not all calls. These contain valuable information about customers, including product and service issues, sentiment, hot issues, trends and predictive behaviors. To obtain a full 360-degree customer view, companies thus need to include analysis of these recordings. In another area, IBM’s work with Watson, its natural-language processing technology, that my colleague has assessed in conjunction with customer analytics could make customer analytics smarter. By using Watson’s capabilities to find and integrate other customer data into a fuller, richer customer view, it could guide actions with even greater detail.

There is no denying that customers have changed their purchasing and communication habits. To keep up, companies need the fullest customer view they can obtain. IBM’s smart customer analytics goes a long way toward meeting these needs. I recommend that companies evaluate how these tools can help them improve all aspects of the customer journey and experience.

Regards,

Richard J. Snow

VP & Research Director

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