Uma Ganesh | October 26, 2020 | 
Organisations are examining what it takes to transform the business on the strength of data, on account of the ability to collect and harness data with relative ease and having recognised the importance of data in business competitiveness. The access to smart digital tools and solutions and the progress in telecommunications technology have had a huge impact on the maturity of data management practices. Despite the several advantages that could emanate from data driven innovation, many organisations continue to face challenges in taking full advantage of the possibilities. The primary challenge is around the definition of data needs, lack of required processes to tap into the data pool and the linkage between various forms of data.
For organisations to become a data-driven enterprise, its important to bring together data from different sources—both structured and unstructured from multiple devices as well as from social media and build robust IT and data architecture to be able to derive meaningful insights. Data quality is most critical with the quality of data determining quality of decision making. However, it is not necessary to wait to start until 100% accuracy on all data is achieved.
The starting point to create trust with the data systems is to have a framework with transparent and clean data that has access rights defined. Data collection and cleaning up should not be seen as a one-time activity and therefore systematic repeatable processes should be put in place with verification and security controls. It is always useful to implement a simple system first that touches all the key functions and addresses the core needs first.
In order to move from one level of data adoption to the next, in addition to putting in place the right processes and technology, getting employees aligned with the mission of the business to be centered around data would be extremely important. To get the buy-in from everyone, data needs to be treated as capital and its use across different functions should be prioritised. Very often employees complain about the lack of basic data or difficulty in accessing the basic data. Building a solution to address this should be the top most priority to get people to believe in the data centered organisation approach.
Companywide data and analytics proficiency should be encouraged and employees should be upskilled as required. As far as possible self serving analytics should be provided to employees so that data becomes a part of their routine and they should be encouraged to explore and discover new facets of doing business on the strengths of the insights drawn from the data.
It is also important to find ways of integrating data science specialists with the functional teams. This could be done by providing data science specialists exposure to business by forming small teams comprising functional and data science specialists and in parallel, make the executives code literate and familiar with the language of data. Data orientation and the resultant business outcomes should be included into performance assessment and reward mechanisms.
For data culture to take strong roots in organisations, leadership should set an example by anchoring their decisions around data and key metrics of deliverables to be measured and monitored should be clearly delineated. Data should become the language of communication both inside and outside the boardroom for data to take strong roots in the business. The ultimate benefit of data driven frameworks would be lowering of costs, streamlining of processes and professionalising the relationships with key stakeholders all of which would result in improved business outcomes.
Originally appeared in Financial Express
