Data is King. This sentence is what amazon, Google, Facebook et al are showing us every day. But what does this mean for enterprises which have a different business model. Data is the key to understand your customer and prospective buyer. On the other hand, data from production can signal early defects in production before they become apparent. If data is king, do we rely on the right data and how defines the right data.
Today we rely mainly on defined data sets. This gives us clear requirements and clear implementations, but seldom we see the real cause, because they are not in the defined data set. With this explicit definition we can gain only the insight we have defined with the data set. KPIs are defined on a fixed data set, but they are only used to match it against the value we got from the month/year before, they don’t answer the why. In a defined data set the why is only questioned in the scope of the acquired data, leaving all the other information behind.
Looking at the data strategy in many companies around the world, we see that the BI builds upon a defined data set. With the predefinition of the question is formulated and room the scope for answers is set. But this kind of analytics doesn’t explain your KPI, it shows symptoms.
Department defines here own silos of information. Some overlap others don’t. All in all, we see that the available information is used in silos and not connected to deliver a holistic view, where different insights can get out the most of this data.
These silos are the base of our product centric business model. This siloed predefined view, to only a part of the available data an enterprise can access, is the root cause for the limited truth of data. The insight gained from this view, doesn’t tell the why it only shows reactions. The shift from product centric to data centric enterprises is not a phrase at all. A data centricity means to get the why out of the data available to your enterprise. Implement the holistic view on internal and external data available to enterprises is a major step to really innovate in the digital domain.
When we talk about the ocean of data, which means all the information your enterprise can access, this doesn’t mean always raw data. There are a bunch of external data providers which take care to consolidate the data for your enterprise. On example is to get a consolidated view how your brand perception is in the real world without conducting surveys, which show only half of the truth. On the hand there is a huge amount of raw data produced every day in a company. Only little of this data is used to get a deeper insight. Some of the data is used to get better insight how your customer/prospective interacts with the information and offerings of your company. But there is always an abundance of data from your production planning and execution which is not correlated but could give you early warnings about future problems or capacity shortcomings or unhappy customers.
The technology to handle big amounts of raw data is already there, but this will not solve to problem of a holistic view. In a holistic view you can correlate early warnings with production quality to the perception of your brand. But this holistic view can enable the evolution of your business model to adapt your offerings to the customers need. It might be possible to allow changes to ordered products much later in the production process, without increasing costs or delay production. Success of campaigns can be destroyed because your production capacity can’t meet the demand. With early warning you are able to match your marketing effort with the production capacity.
Build your enterprise around data is not a task your BI department could fulfil. To move your enterprise in the data driven organization, the first step is to have a holistic view on your enterprise data ocean. To get to this holistic view, analysis of data is no longer driven by a demand of business departments. Analysis of data is proactive performed and demand driven. The proactive part is to find correlations not know before and find the real cause why your KPIs are moving in a certain direction. This new department matches available data sources (intern and extern) to demand and generates insights above this demands to allow the evolution of the business. It delivers the base for evolution and revolution of business model and offerings. It reduces your production costs, because repetitive faults are detected. The goal of this department is always answer the why.
A data driven enterprise can do better forward projection if they learn from the historical data, where the answer the why things did fail or succeed was found. Sometimes business model are too early in time for the customers. Recording the fail and knowing the cause can deliver in future the trigger when customers start considering this business model as option.
Get away with your silo view of data and dive into the data ocean. Get the results out to stay ahead of your competitors. Use your data beyond KPIs and customer analytics.