These are times that companies need to show serious improvement in their decision making processes in turning data into decisions and actions. Even though in a world we talk about artificial intelligence and robots we have gone too fast creating automated decisions in digitalized processes, we still couldn’t catch this flow at companies with organizational hierarchies.
Most of the business decisions are made by humans as they are unstable and should be flexible according to the current situations in operational processes. When making these sort of data related to business decisions it is important to process the operational data as if it is done for raw petrol. At this point, as it is impossible to start a car engine with raw petrol, it is not possible to create meaningful actions for companies who don’t provide data insights for their decision makers.
The increase in data volume is higher than the data that turned into meaningful insights. Within the past year, the companies which have data volume over 100 terabytes had doubled it. We are drowning in the data! However, the companies use only %20 structured data and only %10 unstructured data(social media, contacts, calls, video, sensors,etc.) in their decisions(*). Unfortunately, the % of used data will decrease, if we add filters to these decisions like smart, automated and optimum. The companies stuck themselves to a narrow window when using the data! “Drowning in the data, but not starving for insights” problem is caused by 3 main reasons: human, processes, and technology. The human-related reason is mainly caused by lack of teamwork between Business and IT teams when taking actions to increase data-driven business management process. What has to be done in technology for data management is always the same for years. But due to working dynamics, it is impossible to realize it. As it is always the top priority for new store openings, campaigns, etc. for Business teams. When it is not a priority for Business teams to define an approach to their business management types, It is hard to expect big achievements with IT team’s solutions.
The most critical problem is the lack of the data-driven management approach from top to end decision makers in taking a business decision by looking into the right indicators for each process. When this approach is not adopted, the limited employees or data scientists will not contribute to the company. Even with the simplest BI tools, the results will be either subjective or unrelated to the real business processes.
%66 (*) of the companies keep their reporting and analysis data in excel. In other words, they don’t have a data-driven management approach! Decisions are taken either according to the personal expertise or thoughts on data sets gathered from manual BI tools and/or excel sheets. %34 of the companies get results of their decisions at the speed of business (**). For example, getting data to find an answer on why “A” product sells more than “B” or the profit decrease in “C” category will take with their entire tools and infrastructure. Only %3 of companies can create critical insights.
In order to increase data-driven management approach, it is a necessity to built a system to create calculated indicators and insights for decision makers other than letting them drowning in big data. Otherwise, instead of having as many insights as we can get from our data, we will end up spending more time on analyzing data, calculations and getting insights, getting false results due to personal insights.
Sources: (*)Business Technographics Global Data and Analytics Survey, Forrester, June 2017.
(**) Augmented Analytics Is the Future of Data and Analytics, Gartner, July 2017.