Researchers affirm qualitative data is becoming increasingly insufficient in support of management decisions, amplifying the need to plug in historical data to provide validity of insights. There is nothing more valid and reliable than something that has already happened.
In our private lives, we encounter situations where something goes differently than we wanted, wishing we could go back and change it, we cannot travel back in time; but we consider that event a valuable moment as we use it to shape our future in a better way. In our business lives, we think the same way, the market is now mature enough to provide us with vast information from the remote, but also the recent, and past to make decisions about the future.
The digitalized world is keeping track of what consumer are doing, any time, and any day of their lives. There are infinite touch points recording consumer’s’ behavior, including conversations (online, social media, discussion forums, help desks, etc.), localization (GPS tracking, Closed Circuit cameras, etc.), traffic measurement and much more. Think about the amount of information collected when you enter a grocery store to go shopping without explicitly speaking to an employee they measure the store traffic while your loyalty member app is telling them when you are close to the store and how many times you make a purchase when you are close. The video cameras capture your in store behaviour; when you scan your loyalty card, you are telling them your preferences, your purchase frequency and more. And when you are home? They are still monitoring you.
When you visit the grocery store website, looking for offers and coupons, they store a cookie on your computer that tells them what other interests you have, what other sites you visit, and tailor their direct communication according to it.
Marketers have, at their disposal, nearly the same information of Intelligence agencies such as CIA, NSA, MI6 or Mossad. Are they turning into a sort of intelligence officer? Maybe. Classical research is increasingly matched with data metrics, in a new multidisciplinary approach, to provide insights that are ready to be used for future strategies, namely actionable insights.
Are we, then, talking about Business Intelligence, since we are using an intelligence approach? Or, are we talking about Business Analytics, because we are dealing with data metrics? Let’s understand the difference between the two methods.
Well, let’s first bust the myth that Business Intelligence is an innovation. The very first use of what we now mostly call business intelligence was in 1951, as far as I can tell, with the advent of the first commercial computer ever, dubbed LEO for Lyons Electronic Office, powered by over 6,000 vacuum tubes. And it was already about “meeting business needs through actionable information,” in this case deciding the number of cakes and sandwiches to make for the next day, based on the previous demand in J. Lyons Co. tea shops in the UK. Guess what, then? Even the word actionable is not new. So where is the innovation? The innovation is how you analyze data. What output you produce from it and how you integrate it in the decision making. Originally, Business Intelligence was merely pulling out information from existing sources. Nowadays, new self-learning machines, like IBM’ Watson, can optimize the output according to your needs.
The truth is that anyone is giving its definition of the two names. There is a race of service providers to find the most appealing name for any new data-driven research product, to make it sound more attractive and more marketable, which broadens further the list of definitions.
If we want to find an average definition, that could satisfy different views, we could say that monitoring and tracking metrics and KPIs in the form of reports or dashboards is “Business Intelligence”, but making meaningful sense of these metrics, co-relating them with other factors that influence them, understanding the trends and using statistical algorithms to predict outcomes is where the bang for the buck is “Business Analytics”.
Business Analytics is, in the end, is looking at the phenomenon like Business Intelligence, but it also studies other phenomena that are surrounding and may or may not influence the first phenomenon, delivering marketers information that is derived from seemingly unrelated sources that put Business Intelligence in an unexpected derived context. The value of which is greater than Business Intelligence by itself.