Currently within the consumer packaged goods manufacturing sector, we have what seems on the face to be a paradoxical situation. High-powered Big Data analytical services offer actionable insights like never before, for extremely competitive prices, to nearly all businesses. At the same time, however, the entire market looks very sluggish and stagnant. Although this might seem highly illogical at first, looking at the situation from a novel perspective might lead us not only to a reasonable explanation, but to valuable insights.
In fact, market shares for top ten CPG producers have been declining steadily. Big pushes and promos reap smaller returns every time; new brands have little staying power; and customers continue to look for alternative brands. Given that this comes at a time when CPGs have more analytical tools and info at their disposal than ever before, execs and analysts are understandably befuddled. Could it be that the glut of analytic services has finally whittled opportunity and arbitrage down to nickels and dimes?
It is easy for anybody in business or any other field to view the present with a sense of finality, particularly when the situation is one which has been trending widely and for an extended period. But great innovation is not just possible, it is inevitable. It’s just a matter of perspective. Big Data Analytics may have flooded the market, but there is no end in sight to the potential for innovation in the field. Thus success tilts on the quality/quantity fulcrum.
You hear it all the time; quality is more important than quantity. The key is knowing exactly what you’re getting for your money. So what should you look for in a Big Data Analytics provider? First of all, don’t get dazzled by the size of your provider’s processor. It’s not the size that matters, it’s what they do with it! Algorithms are indeed a very important process within analytics, but who exactly is formulating these algorithms? Are they really doing anything different from any of the other hundreds or thousands of providers out there?
Any provider of Big Data Analytics will have a big gun at their disposal, but few really know how to aim properly. Practices which even a few years ago reaped major rewards for subscribers are now imitated by all providers. Your key to success is to find a provider that continues to innovate their analytical practices.
All data is important to analytics, but it must be configured and processed appropriately to get any truly actionable insights. Last mile configuration may be the most important part of the process. If a provider claims to have automatic customization, or a one-size-fits-all solution, don’t waste your time or money. The foundation for high quality analytics is and always will be personalized solutioning, taking into account key aspects of your business context, business process and information architecture, while focusing on optimizing those outcomes that are relevant for your business and industry.
Another good sign is whether your provider talks about incremental recalibration. Tremendously powerful insights come from processing all the tedious and mundane variations on day-to-day operations. Small things matter quite a bit when you’re dealing with today’s customer. It might be something as simple as product placement. With incremental recalibration processing, you can effectively sniff out these pressure points without sifting through months of data.
Rules management is another one of those Big Data Analytical catchphrases being bandied about. This is a realm where each provider has its specific proprietary algorithm. CPG execs should be as vigilant and inquisitive about this area when picking a provider. The more insightful, intelligent, and flexible the algorithm is, the higher the quality of your Analytics
One major problem with the boom in Big Data Analytics’ application to CPG is over-optimization. This is one of those prima facie paradoxical situations we’ve been discussing all along. Is there really such a thing as too much optimization? Here’s the thing: Optimization is wonderful and will render great profits just so long as it does not come at the cost of real-life experience.
Thus, perhaps the most important aspect of a high-quality analytical service would be experience-based (heuristic) management of data. As they say, there is no substitute for experience – even when this experience is built into extremely complex algorithms on high powered servers. A heuristic approach is one which seamlessly combines the latest in A.I. with real life “brain-based” consulting. Such a configuration is far more likely to render that “magic bullet” for which your CPG competition is awkwardly groping.
Is there a one-stop solution? As this is a quickly evolving industry, one must do one’s own research. A big part of finding the right fit is to find one that is willing to work with your CPG business through all the phases, levels, and changes.