Once an organization has created a solid foundation for data management, it can begin to define clear KPI’s (key performance indicators) and utilize its data for analysis to gain insights that can be transformed into business decisions.
Data analysis contains several layers that are built upon one another to eventually enable an organization to utilize its data and maximize business value. The illustration below visualizes a data-driven scale, reflecting five layers of analytics versus the potential business value.
Ours is a new way of looking at- and dealing with data, providing a ‘Single Version of the Truth’ to act as a guide and companion on our clients’ new data-driven journey. nucleoo is here as the ally In a Traditional phase, organizations typically only look behind and find answers for: What happened? For instance a retailer might look up the sales volume of a particular product over a period of time.
When maturing to a Dashboard phase, organizations have connected a few systems. Although they’re still missing a number of data sources, they start making periodic reports providing analytics for What happened now and then? The same retailer could in this phase compare sales volumes with previous years and identify trends.
In an Analytics phase, organizations start running statistical analysis on their data and find answers to questions like how many, how often and where. In this maturity phase the retailer would probably look into sales volumes of a particular product related to seasons, days in a week and/or where he sold the product. The retailer will also – after merging cost information – analyse profitability of the product.
Organizations start leveraging the predictive power of data in the Predictive phase. What actions are needed? are no longer only decided by gut feeling. The same retailer will start practicing predictive algorithms in this phase and merge his own historical data with external data sources like competitive product information. Based on the insights he gained, the retailer will decide about continuation of-, or price adjustments for the product.
In the Data Driven AI phase, organizations are benefiting from the most sophisticated models like machine learning, deep learning and neural networks before deciding for the best scenario. Ultimately, our example retailer will use the most sophisticated models and gain analytical- and predictive insights of a certain product, for example in conjunction with other (competitive) products or the weather forecast. He will now have the insights to compare different scenarios before settling upon the continuation of the product and define the most favourable place/price/promotion during a given period of time.
What is the best I can do?
Achieving the ultimate stage of data analysis— Data-Driven AI —requires an organization to contract professional resources internally or externally to implement and maintain their data management foundation and data sources. A company like nucleoo helps organizations build the highly necessary data foundation and achieve this final layer. With their cloud-based ‘insights-as-a-service’ tiered offerings, organizations are able to utilize all of their data—including often neglected but insight-rich unstructured data—in combination with external data sources to provide both far-reaching and detailed insights to drive business decisions.