Procter & Gamble is going to quadruple the company’s staff of business analytics experts in the near future. This is despite the fact that the company is reducing spending in other categories, including significant non-manufacturing layoffs and a hefty 30% cut (equaling $1 billion) in annual IT spending.
So why would P&G look to build their analytics ranks so large, so quickly? It’s because they see a new business model emerging, and they’re embracing it.
As P&G CIO Filippo Passerini explained in a recent Information Week article, traditional IT and analytics focused on delivering the right data and reports as soon as possible (usually days or weeks) to key analysts and decision makers. This, of course, is the tried and true model that vast majority of companies are still using today.
What Passerini sees coming is a new model that relies on ad hoc teams of subject matter experts who would assemble, virtually or physically, to address problems the moment they arise. These teams would pull together to handle a specific situation and then dissolve when a solution is reached.
This model is dependent upon a fast and deep flow of granular, real-time data. P&G estimates that right now, they have about 60% of the real-time data they need, and they’re busily working to get access to the rest of it. Much of this data is the typical stuff you’d expect like point-of-sale numbers, manufacturing output, etc. but it’s delivered much faster than is normal for most firms.
In the article, Passerini discusses what Procter & Gamble is trying to figure out in broad terms. They’re ahead of many companies in getting to what I call “One version of the truth,” meaning that everyone agrees on what metrics to use and how to apply them.
P&G is mainly focusing on the next step: given a ‘truth,’ for example, a drop in sales for a particular product, their job is to figure out why. It could be because the overall market has shrunk, or a competitor is taking share, or inventory issues, or a wide variety of other reasons. P&G is working on automating the ‘Why’ piece by alerting product managers to things like competitor moves or production problems.
P&G is hiring analytics pros mainly for the final step – deciding what to do to fix a particular situation. They’re looking for people who will live where IT and business meet. These are folks who understand P&G’s products and markets, and the dynamics of both consumers and competitors.
But they are equally comfortable building models and simulations in order to better understand the existing conditions and the most important factors. With this information, they can recommend the best course of action for solving any P&G problem.
The key to this is speed, speed, and, yes, more speed. In the P&G model, answers and solutions need to be immediate. They won’t take weeks to gather information and formulate ‘what ifs’. In P&G’s world of Big Data, the key players have the data they need to accurately assess the problem and apply the right prescription to fix it or at least improve the situation.
Making the right move at the right time is as important to P&G’s efforts at selling soap as it is to any Wall Street firm trading a multi-billion dollar portfolio – and now firms like P&G are staffing up with the same analytic experts that Wall Street has been hiring for years.