The operational demands and requirements of the fourth industrial revolution have brought a major shift in the modus operandi of businesses globally. The attention has now been focused on data-driven economy as the leverage for competitive edge and continuous relevance.
Kristopher B. Jones, noted that the idea of a data-driven culture treats data as the main resource for leveraging insights in every department of the organization. While companies have always been interested in their numbers, the extent of data use is exercised at a higher level within a data-driven culture.
The main goal of Data-driven culture is to vest all staffs with the capability to actively use data to boost their business delivery goals and to optimally utilize the organization’s potential by making more quality and effective decisions, more impactive initiatives and competitive edge.
The ultimate goal is to build a cultural framework that helps all members of the organization to collaborate to move data at the center of decision-making – from the data owner, to the data scientist, to the business analyst and finally to the employees who use it in their business department. This encompasses coming up with new, data-driven use cases, discovering patterns in data and experimenting with analytics solutions to see what really works in operational processes.
According to New Vantage Partners’ Big Data Executive Survey 2017, only 37% of companies who pledged to become more data-driven, have actually successfully accomplished their goal.
David Waller revealed that the biggest obstacles to creating data-based businesses aren’t technical but cultural while Laurence Goasduff noted that launching a data-driven culture is a matter of influencing mindset and behaviors rather than of control. And therefore , to establish a data-driven culture change in any organization, it requires engagement with stakeholders to secure buy-in and ongoing support in treating data as an asset — not data as a byproduct.
To manage the process of advancing data-driven culture, three strategies must be noted 1)Identify and communicate the business value of data,2) Address the cultural change impacts of a data-driven approach and 3) Manage the ethical implications of data and analytics
Identify and communicate the business value of data- this involves the process designed to measure information’s key quality attributes, which include accuracy, validity, usability and its relevance to key business processes. At the same time, they need to determine the actual impact on business KPIs to better prioritize and support information asset management initiatives.
Address the cultural change impacts of a data-driven approach- As part of establishing a data-driven culture, management should be responsible for the culture change to support the transformation. But they cannot simply tell people to change their culture — they must inspire people to believe that change is necessary.
Manage the ethical implications of data and analytics -management can establish a code of conduct that defines ethical guidelines for the use of data and analytics. Balance the opportunities and limitations between the benefits of data and analytics and the ethical and privacy risks they pose. Finally, be clear about any trust expectations.