by Ronald Mueller October 13th, 2017 0 comments

Inducing Data Driven culture into an organization is the key to making fact based decisions. It is more often easily said than followed as this is not a one-time process, but requires an ongoing combined effort from both the employees and management. Management should foster the muscle to take initiative in bringing about an organization wide transformation on how to use data and analytics that yield better decisions.

So how can an organization transform its culture to become data-driven? According to Burak, a solution architect at Macrosoft and leader in building data analytics solutions, this is more of a human problem than a technology one. Companies should make it very clear what their business objectives are, how they are going to align their measurement plans, and what are the key performance indicators that need to be watched during this transformation journey. 

Just because organizations have been generating lots of reports, does not make them data driven as the data was not democratized. What we mean by democratized is that the data was sitting in the hands of select few who were creating periodic reports or dashboards, which was kept in an inactive way or worst ignored as the reports delivered little to no value to the organization. Most reports and dashboards are either not well structured or not projecting a clear picture of what has to be done in order to take on the challenges faced by businesses. Reports and dashboards are simply not enough to define data-drivenness. 

 Analytical value chain is the key for any data-driven organization as it is completely rooted in organizational culture. Culture is the main aspect that sets expectations to what extent data is democratized, how data is viewed across organizations, and how it is positioned as a strategic asset in training resources. As data forms the basic building block, collecting the right data having adequate quality is really important. Main consumers of this data are the analysts and data scientists whose primary task is to generate insight from the data. 

 Organizations have to move on to a data centric culture that challenges assumptions, discusses critical issues leading to iteration, and recognizes anyone who can generate good data. By incorporating a data-driven culture companies are entitled to a host of benefits. It helps businesses understand how data driven culture provides employees with the capabilities and skills they need to analyze data to generate meaningful insights, leading to a more accurate decision-making process. Creating such a data-driven culture enables employees take on an active role to seek out more apt data that help fine-tune strategies and objectives.

 Companies need to follow a business-aligned culture that supports data storage and the way employees access this data that is crucial for any business to perform. What is required is distributing the data across the functional departments of the organization, discussing it in detail and being able to understand how analytics can bring about a transformative change. Companies will have to ensure that there is data flow within the organization, engaging the entire staff with the way information is ingested and communicated across departments, to help cultivate a new era of improved performance. 

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about the author: Ronald Mueller
Ron is CEO and Founder of Macrosoft, Inc.. Ron heads up all company strategic activities, and directs day-to-day work of the Leadership Team at Macrosoft. Ron is also Macrosoft’s Chief Scientist, defining and structuring Macrosoft’s path forward on new technologies and products, such as Cloud; Big Data; and AI. Ron has a Ph.D. in Theoretical Physics from New York University, and worked in physics for over a decade at Yale University, The Plasm Physics Lab in Princeton, NJ, and at Argonne National Laboratory. Ron also worked at Bell Laboratories in Murray Hill, NJ., where he managed a group on Big Data, including very early work on neural networks. Ron has a career-long passion in ultra-large-scale data processing and analysis including: predictive analytics; data mining, machine learning and neural networks.