Putting advanced analytics to work
Putting Big Data and advanced analytics to work promise to transform the way many companies do business, delivering performance improvements not seen since the redesign of core processes in the 1990s. As such, these tools and techniques will open new avenues of competitive advantage. Many executives, however, remain unsure about how to proceed. They’re not certain their organizations are prepared for the required changes, and a lot of companies have yet to fully exploit the data or analytics capabilities they currently possess. Getting leaders’ attention Big data and analytics actually have been receiving attention for a few years, but the reason is changing. A few years ago the question was “We have all this data. Surely there’s something we can do with it.” Now the question is “I see my competitors exploiting this and I feel I’m getting behind.” And in fact, the people who say this are right. If you look at the advantages people get from using data and analytics—in terms of what they can do in pricing, what they can do in customer care, what they can do in segmentation, what they can do in inventory management—it’s not a little bit of a difference anymore. It’s a significant difference. And for that reason, the question being asked is “I’m behind. I don’t like it. Catch me up.” I get asked, “Who’s big data for?”
Finding better answers
So where have we been seeing data analytics recently? Well, the answer is in many places. An airline optimizing what price it charges on each flight for any day of the week. A bank figuring out how to best do its customer care across the four or five channels that it has. Allowing customers to be able to ask questions and get better answers and to direct them. All of that is on the customer side of things. And then in operations, think of an airline or a railway scheduling its crews. Think of a retailer optimizing its supply chain for how much inventory to hold versus “What do I pay for my transportation costs?” All of that lends itself to big data—the need to model—but frontline managers have to be able to use it.
Changing the organization
So what’s the formula or what’s the key success factor for exploiting analytics?
It always comes down to three things: data, models, transformation. Data is the creative use of internal and external data to give you a broader view on what is happening to your operations or your customer. Modelling is all about using that data to get workable models that can either help you predict better or allow you to optimize better in terms of your business. And the third success factor is about transforming the company you’ve developed a new model that predicts or optimizes, how do you get your frontline managers to use it? That’s always a combination of simple tools and training and things like that. Then there’s a medium-term challenge, which is “How do I upscale my and things like that.
Executing big data
There are several things you just have to do. The first is you need to focus. And what we mean by focus is, let’s take a pricing manager in a consumer services company or a buyer in a retailer. They have 22 things they do. Don’t try and change 22 things; try and change 2 or 3 things. Focus on part of the decision and focus, therefore, where the greatest economic leverage is in the business. The second is that you’ve got to make a decision support tool the frontline user understands and has confidence in. The moment you make it simple, understandable, then people start using it and you get better decisions. For a company, if you have 100,000 employees and you’ve got only 14 that actually know this stuff and how to use it, you’re not going to get sustainable change. You don’t have to have 100,000. But you might have to have 10,000, five years from now, that are comfortable with analytics. So, again, link it to the processes, get the metrics right, and make sure you build the capabilities across the company.