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		May 5, 2011	ANNOUNCEMENTS Submissions for the next Business Intelligence Journal are due May 20. Submission guidelines CONTENTS Is Business Intelligence Strategically Important? Segmenting Office Integration Technology Mistake: Ready, Shoot, Aim: Failing to Design Data Governance See what's current in TDWI Education, Research, Webinars, and Marketplace
	Is Business Intelligence Strategically Important? Steve Williams DecisionPath Consulting
Topic: Business Sponsorship The Corporate Executive Board (CEB) reports that many IT opportunities over the next five years will be driven by business intelligence (BI). CEB surveyed large companies in a wide range of industries, and the clear trend is that companies will see many BI opportunities as well as a relative de-emphasis on using IT to automate business processes. This means the CIO’s focus should move toward helping business customers leverage BI to drive profits. There are a variety of strategic challenges IT executives will face in this regard, such as determining the strategic importance of BI. Our experience as BI consultants has shown that business leaders are sometimes reluctant to fully pursue business intelligence. This reticence prompted me to revisit the question of whether BI is strategically important, which affects the willingness of business executives to sponsor and fund BI. For the IT executive, getting clear guidance and a concrete mission for BI is a function of engaging business executives on this subject. Factors That Increase the Strategic Importance of BI In general, business intelligence and business analytics are tools for understanding, planning, controlling, and improving business performance. The strategic importance of BI increases as a function of business complexity. In general, the following factors contribute to business complexity: The number and diversity of individual customers a company serves The variability of the demand for a company’s products or services The number of products a company sells The number of suppliers from whom products and/or services are obtained The number of geographies in which a company operates The number of business units a company has The number of industries in which a company operates Essentially, BI is more strategically important the greater the complexity of the business or industry, and less so the more straightforward the business. Over time, companies that master the complexity will outperform companies that can’t make optimal decisions because they lack the information and analytical tools (i.e., BI) to understand and drive their results. To illustrate this idea, consider Company X, a fictitious $9 billion financial services firm with millions of clients who have 401(k) accounts in employer-sponsored plans. Company X: Has millions of clients at different life stages and with different investment attitudes Sells through a national network of more than 1,000 financial intermediaries, some that sell a great number of 401(k) plans and others that sell only a few Sells 401(k) plans that have a variety of customizable features Offers a number of channels (Web, call center, and financial representatives) through which clients can interact with the company to make changes to their 401(k) elections Under this scenario, which is similar to an actual situation we encountered, the strategic importance of BI is arguably high. By understanding its millions of clients better, Company X is in a position to grow and retain their business over time, which helps revenues and profits. On the other hand, consider Company A, a fictitious $500 million contract manufacturer of three similar, fast-moving natural products, which it sells to three large national natural product retailers via one national distributor. In this scenario, which is also similar to a situation we came across, the strategic importance of BI could reasonably be judged to be low. Company A: Has only one customer Makes only three products Faces a simple demand pattern Has a simple conversion and packaging process Has straightforward inventory and supply chain processes Company A could use BI to optimize its demand planning, purchasing, and inventory management processes and performance, so some level of BI investment is warranted. On the other hand, as long as the company has sufficient business information and analytical tools to effectively get the product out the door, its strategic and competitive performance will be fine. Checklist for Engaging Business Executives on the Strategic Importance of BI To make progress in leveraging BI in such areas as finance, HR, operations, supply chain, customer service, sales, marketing, and product/service innovation, it is critical to establish executive consensus on the strategic importance of BI. Here is a checklist CIOs can use for doing so: Analyze the strategic importance of business intelligence for your company and industry using the complexity factors listed above. Develop a short presentation about why business intelligence is important to your company, using examples from across the company that illustrate gaps in your company’s ability to measure, manage, control, and/or improve important aspects of functional and/or enterprise performance. Share the presentation in informal ways with company executives, asking them to provide feedback about areas of agreement and disagreement, and to provide their ideas about the strategic importance of BI. Ask executives to predict the business consequences (or adverse impact) of not according BI the correct level of strategic importance. Provide an executive overview of BI and its potential impact on profits and performance, using case examples Executive Consensus on the Strategic Importance of BI Creates Key Conditions for Success Once business executives decide whether BI is strategically important, they can work with the IT executive to devise the appropriate BI mission, which drives investment levels and timing. Consensus on the mission builds an appropriate degree of urgency and commitment to change. If executives agree that BI is strategically important, it will be much easier to gain business sponsorship, funding, and the engagement of appropriate business people in the BI design, development, and deployment processes. All of these factors contribute to BI success. Steve Williams is president of DecisionPath Consulting, which specializes in business intelligence, analytics, data warehousing, and performance management solutions. Contact Steve at 301.926.2452. Highlight of key findings from TDWI's wide variety of research Segmenting Office Integration Technology Starting in the early 2000s, BI vendors decided to embrace Microsoft Office instead of resisting it. They added one-button exports to simplify the process of dumping raw data from queries or reports into Microsoft Office applications, especially Excel. They then created add-ins that made it possible for users to view, interact, and refresh BI reports from within Excel, PowerPoint, Word, or Outlook. To appeal to power users, they also turned Excel into a full-fledged client of OLAP and relational databases, using the BI server as a query and metadata engine. The quadrant chart below shows the range of technologies available today for integrating Microsoft Office and BI tools. (See Figure 9.) The chart shows which technologies are appropriate for casual users--those who generally consume reports created by others--and which are appropriate for power users--those who produce reports and analyses. It also segments the technologies by the degree to which they support a managed BI environment, where data and rules are managed centrally rather than on the desktop. A managed BI environment minimizes the potential for users to create spreadmarts and wreak havoc on data consistency. (Click to enlarge) Source: Strategies for Managing Spreadmarts: Migrating to a Managed BI Environment (TDWI Best Practices Report, Q1 2008). Click here to access the report. FlashPoint Rx prescribes a "Mistake to Avoid" for business intelligence and data warehousing professionals. Mistake: Ready, Shoot, Aim: Failing to Design Data Governance By Jill Dyche and Kimberly Nevala As with any strategic initiative that enlists both business and IT and is process-centric and highly visible, data governance must be designed. Designing data governance means tailoring it to your company’s specific culture, organizational structure, incumbent ownership environment, and current decision-making processes. It means articulating the value proposition for cross-functional and formal decisions about corporate information--whether by minimizing compliance exposure or security breaches, over- or under-communicating to customers, consolidating product catalogs, or supporting dozens of other potential business drivers. No two companies treat these issues in exactly the same way, and data governance is never exactly the same across companies. Consider two of our clients. One client, a multinational bank, is hierarchical and formal. Decision making is top-down. Budget sign-off goes high up in the organization for relatively meager expenses. Executives are big on “town hall” meetings and roundtable discussions. Consensus reigns. The other client is a high-tech firm where even business execs are tech-savvy. People come to work at 10 p.m. with a six-pack, the dog, and some really good ideas, and start coding until 10 the next morning, when they’ll toss the empty beer cans in the recycling bin, load the dog in the back of the Subaru, and head over to the trailhead. These guys fix their own problems and make their own decisions. Anarchy is the rule. Data governance looks very different at these two companies. At the bank, three different governing bodies are involved in the data governance process, each with its own checks and balances. The high-tech company relies on established yet grassroots effort. The stewards use an online knowledge base to submit decisions for review, subject to occasional tie-breaking by executives. These stewardship units are endorsed by divisional managers, who want to see measurements for data quality, integration, and deployment velocity improve. If we had arrived at either of these companies with a “best practice template” for data governance, we would have been met with rolled eyes and the requisite explanations of “why we’re different here.” The high-tech company would have laughed us out of the espresso lounge, had we recommended a single business sponsor. Conversely, the bank requested a formal mission statement with formal hand-off points across different committees for its governance council. In both cases, deliberate data governance design ensured that governance supports the company’s culture, organizational structure, implicit hierarchies, and way of doing business, while making sure its value is well understood and ultimately measurable. Source: Ten Mistakes to Avoid When Launching a Data Governance Program (Q1 2008). Click here to access the publication.