This is achieved by deploying data and analytics to translate complex data into meaningful insights that enable more purposeful customer engagements and business decision making processes.
Therefore, organisations need to make the right choices up front – consider the use of interoperable technologies, set up coding standards and govern the choice of programming languages.Organisational readiness, buy-in, and very importantly, sponsorship remains key to setting up a successful data and analytics capability. This is usually the first and most important step to get right, for any data and analytics capability, to attract investment, grow, scale, and survive in an organisation.
Once a true data culture has been built, the organisation needs to avoid the temptation of second-guessing data-driven decisions – if this dominates in an organisation, the data driven culture is likely to have a slow death overtime.Work needs to be done, continuously, to improve data literacy across the organisation. This does not mean that everyone needs to be a data specialist, however, the basics of data and the value of data in solving business problems needs to be understood.
Furthermore, the data and analytics teams need to understand the bigger picture and the way in which their contribution translates into the organisation achieving its strategic imperatives and delivering on commercial performance.Analytical capabilities are often ring-fenced and centralised as a centre of excellence for various reasons. However, this centralisation should not translate into the unintended consequence of creating both physical and psychological barriers for integration.
It is important to give equal opportunities to individuals in the organisation – parachuting individuals without giving opportunities to existing teams will undoubtedly destroy the team morale – this can have disastrous outcomes from the onset. The managers need to have a passion for driving adoption of data and analytics to ensure that their teams are working on meaningful use cases, translating business problems into the language of data and the data into actionable insights and tangible benefits.