Written by Karl von Beckmann
Are you driving down the road looking in the rearview mirror?
Many companies are leveraging the power of business intelligence to serve a number of key functions in their organizations: They may use it to share important information across teams to come to decisions on how to react; they may use it to provide dashboards to executives so that they are able to monitor key company metrics in real time; and they may use it to deliver important information to important external stakeholders, like partners or suppliers. This flow of information is the lifeblood to a modern company’s operation plan. However, there are natural limitations to this. The analogy would be trying to drive down the road while only looking in the rearview mirror. All you can see is what has already passed. It’s possible to infer that because the road behind you is paved, that the road ahead must be as well. But this in many cases is pure speculation!
Now, some may argue that this is a bad analogy. Because unlike driving in real life where it is possible to see the road ahead and anticipate what is coming, it is impossible to see ahead into time to predict what is coming for your business. However, today’s technology is making it possible to actually look ahead into the future of your business. And it is called “predictive analysis.”
Predictive analysis is in fact nothing new. Companies and institutions have been making good use of statistical analysis for years to identify trends in order to predict future situations or behavior. Such infamous recent examples include the retailer who knew one of its teen customers was pregnant before her own father did.
The applications of predictive analysis are essentially limitless. With the massive volumes of data of all kinds being captured in today’s world, it is possible to create predictive models for almost any conceivable question.
So why isn’t everyone making use of statistical analysis?
The truth is that it’s just not that easy. Traditionally, professional statisticians are employed (many of them with advanced academic degrees) to pore through heaps of data in order to identify correlations and trends. Then they need to design complex algorithms which then need to be tested, and tested again for accuracy. Finally after much manual arithmetic and calculation, some hypotheses are developed which may be able to accurately predict a future trend.
Where this practice tends to break down is in its scalability. With the staggering volume of data needed to create a predictive model, one person or one team of statisticians can only feasibly work through so many problems at one time. This typically means that only the most pressing issues in a business will get the attention of the predictive statisticians, which of course leaves the rest of the business to fend for themselves.
Predictive for All
Clearly, the opportunity exists to bring this type of predictive analysis to the wider business. This is exactly what has prompted SAP to create SAP Predictive Analysis. With Predictive Analysis, SAP has introduced the power of foresight to the businessperson. Whether you are in HR, or sales, or marketing or operations or any other line of business, you now have the option of asking and getting answers to the questions not about what happened yesterday, but about what might happen tomorrow.
The advantage of driving forward looking questions from the business standpoint as opposed to the analyst or statistician’s standpoint is one of expertise. While the statistician is able to draw wider assumptions and trends based on the macro points of the business, the business person is far more familiar with the important details which can have an immediate impact. As an example, a sales vice president might know that one of his top sales reps is due to deliver a baby in the next 3 months and that she plans to take a 6 month maternity leave. This is information that a statistician would likely not have when developing a sales forecast. However, the VP knows to take that rep’s contributions down for the period of the maternity leave. This would make the business driven calculations more theoretically accurate than the centrally produced prediction.
This is just one of thousands of potential scenarios where business people could potentially drive powerful and accurate projections based on historical data and their domain expertise.
This natural evolution of what is possible with data is a significant and exciting development for all businesses that derive insight from their data. It represents a momentous shift in paradigm for business people and leaders who can now orient their organizations and decisions around what is to come. Those who are ready to lift their eyes to the road ahead stand to reap significant competitive advantage over those who continue to speed along looking only behind them!
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