This post is part 1 of 2

The first data mart I created was back in the late 1990's. I did everything right (or at least by the book). The users knew what they wanted, the data existed, the ETL tool was adequate and the data model came together like a dream (a geeky dream, not a cool dream like having super powers or winning the lottery). I was stoked! We unveiled the masterpiece to our stakeholders to great fanfare and excitement. Then, a funny thing happened over the next 6 months. It barely got used. I had a hard time accepting this, and pushed for answers (my wife says I do that a lot).

Here is what I learned: It turns out that having a full set of easily attainable requirements doesn't always mean you are creating something of business value. In my case, I was creating a data mart and BI solutions that were based on what was already known. Sure, the data was now easier to report on since it was consolidated, so the users thought it was a great candidate for a data mart and a BI solution. Once it was in front of them, they were mildly impressed and basically went back to just pulling standard data from pre-defined parameterized reports. They were less interested in navigating, data mining, and performing what-if analysis than I was anticipating.

Fast forward 12 years and many failures later...I've come to realize that the most valuable epiphanies in business are much like those in our personal lives. The combinations of things taken in new ways create wonder and enlightenment. Consider your own experiences. Do you remember the first time you had strawberries with cream? How about a sandwich with mayonnaise? Did the discovery of ketchup impact your creativity and desire for lunch as a child? Did new options and combinations come to mind? Did you open up to new possibilities and explore the wonders of food? I know I did (wish I could stop now that I'm...ahem...older).

I submit that "real" BI is reaching into our companies' data refrigerators and coming up with new combinations of business facts and dimensions to create wonder and enlightenment. Unfortunately, most BI vendors and industry research firms (the usual suspects) would have us retreat to the safety of the most common and well conformed data in our companies. This helps guarantee success of the warehouse, or the data mart. But when was the warehouse our finish line? When did completing a well modeled data mart become the value in the BI chain? It hasn't. We need to own up to that and realize that the reasons to create BI data structures are to promote the extraction and discovery of business value from them. Without that, we are presenting users with the same peanut butter sandwich on wheat bread that they have eaten for years.

Look for Part 2 of this blog very soon. In the meantime, reply with thoughts or experiences in this area. I'd love to hear them. I'll be here eating my pickle-banana-tomato sandwich while you type.

BI And the Internet Of Things

Posted by mmy Apr 12, 2010

After reading "The Internet of Things" from The McKinsey Quarterly, I couldn't help but think of how real time business intelligence will play a strong role in making sense out of all of the new information that is becoming available so that organizations can drastically improve the way they do business.

One of the main points that the McKinsey article makes, is that "more objects [such as roadways, medical devices, energy meters etc.] are becoming embedded with sensors and gaining the ability to communicate." BI solutions will need to be capable of accessing and integrating this type of information with other available data in near real time in order to best improve decision-making. Much of the BI of today is still too slow, providing answers and reports in days and weeks, rather than the instantaneous feedback that is necessary to avoid losses incurred over those time periods.

Consider persons, receiving care for a health condition, who have been outfitted with sensors that transmit real time vital signs. Rather than relying on tests done at the time of a doctor's visit, continuous monitoring ensures that early warning signs are not missed. Alerts can be provided for the patient and the hospital at the earliest sign of warning. With real time BI, information about the effects and results different treatments have on various segments of patients, can be reported and analyzed immediately by all doctors within a given network.

"Some auto insurers are already offering to install location sensors in their clients cars so that their auto insurance rates can be based on driving behavior rather than age, gender and place of residence." Okay, but let's take this one step further. With effective BI, insurance companies could combine this information with other risk information to decide which clients it would like to cross sell life and disability insurance products to. Furthermore, with near real time analysis, alerts could be sent to immediately flag an identified high risk policy from being renewed.

Regarding manufacturing facilities, time of use pricing data is becoming more available allowing for more accurate costing than fixed rate energy consumption pricing. Executive dashboard BI tools that analyze and display for example, the actual energy consumption costs per production manager, location, and time could be used to evaluate performance and bonus consideration.

Sensors and videos at retail displays are starting to be used to optimize merchandizing. Consider the benefits of feedback from a promotional display for cereal to let you know that the display attracted the attention of 100 shoppers on a given day. Integrate that data with POS data that indicates that 10 such cereals were purchased that same day. Now consider a BI tool that associates this data with the number of total shoppers that entered the store that day and the demographics of shoppers that made and did not make cereal purchases. Compare similar and different displays at other stores with similar and different customer demographics to determine the best display for each store.

The effect of Moore's law is helping to reduce the size and cost of sensors and actuators. Likewise it is reducing the cost of BI solutions to produce real time analysis and reports of larger volumes of more complicated data associations. These two aspects make for a very exciting future, where the biggest limiting factor will be the creativity and imagination of the end-user.

The internet has empowered consumers to quickly access pricing information from a wide variety of retail competitors. Additionally, rapid advancements in technology and the sharing of such information have shortened product life cycles. These two factors have made it difficult for retailers to maintain their margins unless they discover and implement tactics to create and maintain a competitive advantage.

One way that Best Buy was able to create such an advantage was by using a best of breed business intelligence approach to provide instant visibility into sales and profits by product, region and store over a product's life cycle. This expedited Best Buy's ability to determine and discontinue those products that had reached the end of their life cycles. Moreover, executives and managers were also able to determine the ability of marketing campaigns to bolster sales for specific offerings at each store. This type of information is visible to executives each day and actions can be taken immediately to optimize marketing mixes and product margins rather than waiting for a less granular report at the end of the month.

Another competitive advantage of Best Buy's BI capabilities centers around loss prevention alerts and instant awareness regarding gross undercharges. For example if a $2,000 flat screen TV is mistakenly sold to a customer for only $200, how quickly can this anomaly be detected and corrected before it is repeated again and again? Furthermore, how quickly can the cause of this type of defect be determined (i.e. a promotional misunderstanding, human error, or criminal intent) so that similar such incidences do not occur.

I attended and spoke with a number of retail executives and managers who viewed the Stores knowledge Series Best Buy Webinar on 3/23/10. Many of the executives I spoke with were using traditional business intelligence and/or manipulating Excel spreadsheets, and they expressed frustration regarding the time it took to get reports and answers that they needed. The issue regarding alerts and instant visibility into gross undercharges is worthy of further scrutiny since such defects and their effects can remain inconspicuous in a vast sea of disparate data.

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