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<p><b><font face="Verdana,Arial,Helvetica" color="#336666" size="3">Putting the e in eBI</font></b></p>
<p><b><font face="Verdana,Arial,Helvetica" size="2" color="#666666">What is unique about Business Intelligence for Web-based enterprises?</font></b></p>
<p><font face="Verdana,Arial,Helvetica" size="1">Technology-assisted, hands-on analysis of business data goes back at least 30 years. As business needs evolved, and as technology advanced, the terms describing this activity changed but the core essence of the practice remained the same.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">Analytic services gave way to end-user computing as fourth-generation languages (4-GLs) and the first wave of dimensional tools replaced hard-core statistical packages on the mainframe. End-user computing morphed into decision support while client-based graphical tools took hold and data stores proliferated. Decision support was subsumed under the more ambition label of business intelligence as the second wave of dimensional tools (now called OLAP) joined the growing plethora of reporting and analytic options.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">Then the World Wide Web changed everything.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">Technology reversed back to a network and server-centric model. Every vendor fought to catch up then one-up the competition by defining a new “paradigm”. All tools had to become web-enabled until that was not enough and everything had to go native.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">But the real change was in the nature of business itself. eBusiness is the more mature outgrowth of the dot.com frenzy and its here to stay. And it is fundamentally different in several ways we know of and many more we are yet to discover.</font></p>
<ul>
<li type="disc"><font face="Verdana,Arial,Helvetica" size="1">How will the practice of business intelligence change to support this novel, volatile, evolving and unpredictable business model?</font>
<li type="disc"><font face="Verdana,Arial,Helvetica" size="1">Will the seemingly seat-of-the-pants, cowboy mentality of eBusiness change with the incorporation of this more left-brained activity? Is this good or bad?</font>
<li type="disc"><font face="Verdana,Arial,Helvetica" size="1">Is it even fair to cast this new form of analytic activity in such a geeky fashion when more intuitive and creative elements are incorporated?</font>
<li type="disc"><font face="Verdana,Arial,Helvetica" size="1">I can only scratch the surface of these questions in this article. Let’s start by defining the unique aspects of eBI.</font>
</ul>
<p><font face="Verdana,Arial,Helvetica" size="1">Business Intelligence for eBusiness has several focus areas: economics, exploration, and enablement. Economics involves implementing the (often missing) infrastructure to capture and track performance data. Exploration entails a discovery process that interrogates all data captured via interaction with the site, participant profiles, partner data, market information, and other external factors. Enablement involves deploying dynamic processes to create new business opportunities.</font></p>
<p><font face="Verdana,Arial,Helvetica" color="#336666" size="2"><b>Economics</b></font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">The dot.coms that survive will be those that build a viable economic model and manage their businesses accordingly. Entrepreneurial zeal gets the companies started. Operational effectiveness will ensure their long-term success. The practice of eBI could start with the basics of performance tracking.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">The end goal is to initiate momentum towards profitability. This is what the market is demanding now. Building a market and locking in customers in not enough unless costs can be managed and revenue can be grown aggressively.<br>
</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">The dot.coms have the advantage of minimal infrastructure (no out-of-sync legacy applications) and relatively simple monetary flows. This makes it much easier to implement tracking mechanisms once profitability targets are set. Well-established techniques can be applied that leverage traditional BI skills. We have to build form scratch but in very familiar territory. </font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">Introducing economic accountability into the Internet ventures of a brick and mortar company is far more difficult. It is difficult to segregate the revenue streams and expense accounting of the eBusiness from the existing business. Often shared costs are assumed by the traditional business and an overly aggressive allocation of revenue is made to enhance the apparent success of the eBusiness wing. Spinning out the eBusiness division is the only sure way of creating divisibility of economic results.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">As long as the eBusiness is still within the existing corporate structure, eBI is more difficult but also more essential. A detailed operating model must be constructed that goes beyond simple allocation of costs and revenues. Transaction by transaction, costs must be attributed to the old or the new business. Where the costs are truly shared, they must be tracked separately to see how material they are to the profitability of the eBusiness based on how much of the cost is allocated.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">At first, it seems that revenue should be easy to apportion. Revenues from web site advertising and transactions go to the eBusiness while retail store revenues go to the existing business. But it gets murkier as you look deeper. How do you handle cross-promotions where the web site encourages increased retail traffic such as via web-delivered retail coupons? How about when retail outlets sell low margin equipment while referring customers to the web-site for high margin (but high inventory cost) supplies? The role of the eBI process is to detect, monitor, and analyze these differential impacts on profitability.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="2" color="#336666"><b>Exploration</b></font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">An eBusiness throws off a lot of data. Click-streams, inquiries, orders, support requests, and interactive contacts to name a few. These can be very rich data streams because we get the who, what, when and where of each event. We can also get “how long”, “how much”, and “what for” information in some cases.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">Even more importantly, we can get the entire lifecycle of interaction with a given customer from a single source. This has been virtually impossible with traditional businesses that touch a customer in many different ways from different departments on diverse and non-integrated systems.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">The eBI challenge is to make sense of this rich but raw base of data. The first essential task is to clearly articulate all your touch points with the customer. You build a lifecycle model that accounts for all the stages of interaction from first signup to account termination if you lose them. Within the overall customer lifecycle are buy/interact cycles. These repetitive cycles have stages that apply to each product from inquiry to order to delivery to support requests to returns. Other cycles apply to other forms of interaction.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">The purpose of lifecycle modeling is to ensure we can chain together all the data for a customer and each sequence of interaction. It would be a crying shame to finally have an environment that promises holistic and integrated information but then fails to deliver because of business process or data design oversights.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">The second step is to build a dimensional model using published and proven methods. The dimensional model helps you monitor progress towards defined targets within a formal analytic structure. It can also be used to identify and set new targets.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">One essential variation is to build from the detail up without the disconnection that results from intermediate aggregation. Our first implementation is always a detailed star-schema to preserve maximum flexibility during initial discovery and dimensional refinement.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">When you have identified repetitive business processes, you should invest in an OLAP tool of your choice. The introduction of this technology is primarily for performance management and to provide enhanced out of the box functionality for analysis. It is important that you NOT move to implement OLAP tools until you are ready to lock and load. You must first achieve a degree of stability in your dimensional design and you must understand the business processes you intend to support. The introduction of the tool provides many advantages but it will definitely restrict your flexibility once implemented. </font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">The greatest potential can be realized using data mining techniques. One of the promises of eBusiness is to analyze the patterns of customer interaction to identify marketing opportunities. Data mining tools are just now coming into the mainstream. The limiting factor will not be the technology; it will be your imagination.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">The simplistic view of data mining is that you pour undifferentiated data into a cauldron, stir as it boils and bubbles, wave your hands over the brew, and, voila, a conjecture materializes. Unfortunately, data mining is hard work despite how easy the tools may be. You must define an analytic framework and select the decision variables. This is where imagination comes into play. If you do not collect and include the right data, you may get inconclusive, or worse, incorrect results.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">Let’s try an example. Consumer commerce sites would like to encourage impulse buying. They do this by displaying targeted offerings when you return to their site. Without data mining, a basic technique is to offer you items like what you have bought before. If you have ever bought Pokemon cards, the site may offer more Pokemon material or other children’s toys. This can be very annoying to someone who bought these cards once for a nephew and does not buy regularly for children.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">Now say you use a data mining tool and include “number of children” and “number of purchases per category” as variables. The tool is likely to predict that people with no children will generally buy fewer toys. Duh! How do you identify people who are more likely to buy toys online and respond to an impromptu solicitation?</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">What if you add marital status to the mix? Okay, in advance you expect that married with children obviously buy more toys. When the results are in, you might find that divorced parents buy more online than married parents. This is a more meaningful result. Including sex might reveal, as one company found, that divorced fathers are far more likely to purchase toys online than any other segment by a large margin. They are better candidates for online promotions.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">When the results are in, many conclusions from data mining seem self-evident. But you can’t prove them apriori. You will also never find these relationships unless you have the foresight to feed the data mining engine the right factors in the first place.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1" color="#336666"><b>Enablement</b></font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">The final category, enablement, refers to exploiting business intelligence methods dynamically as a part of doing business. BI is no longer just an optional, adjunct analytic process. It becomes a method of defining, tracking, and revising new programs and new business opportunities.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">In last months article , the topic of closed loop analysis was introduced. This is an aspect of eBI that supports just-in-time decisions and continuous revisions. This is a tightly coupled process where analysis spawns execution and the results of executing a tactic become fodder for follow-on analysis.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">A meaningful example is deploying an active customer retention program. With many traditional businesses, growing customer-share is far more valuable than gaining market-share. It is more cost effective to sell more to existing customers than recruit new ones. This is a hard won lesson that is only now coming to the attention of Internet enterprises.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">eBusiness has followed the example of telcos and ISPs by aggressively targeting new customers. Dominating a market niche has been the mantra of eBusiness. This tactic has worked for a few lucky ones but at extremely high cost. Reducing churn, the measure of customers coming and going, is not just a business goal, it is a survival tactic.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">What will keep customers coming back to your site? People have no investment in the relationship and the cost of playing the field is virtually zero. You have two options, expand or enrich, and both are enhanced by eBI. eBI can be exploited to reduce the cost of expansion into new markets but this is more of an intuitive than data-driven process. It is far more effective at tracking progress to confirm a success or to cut your losses early.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">Enriching the experience of existing customers is far more amenable to eBI integration. Enrichment involves adding new features and services that set your site apart from all others. This is an incremental process of continually refinement. Targeting, testing, and tuning of the new offerings allows you to both generalize and customize. You generalize by identifying those features that appeal broadly to existing customers and help attract new ones. Customization entails identifying narrow segments of your customer base that respond more favorably to a particular new facet.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">eBusiness is the first business sector to live and die by information presentation. Once the infatuation phase is over and customers become more discerning, Business Intelligence will become the dominant profession of the Internet Information Age.</font></p>
<p><font face="Verdana,Arial,Helvetica" size="1">We will explore eBI in more detail in future articles.</font></p>
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