Data is still growing exponentially and data sources are increasing in number, size and complexity. There are ever-increasing demands on how new innovations, such as artificial intelligence (AI) and machine learning, can be harnessed across the organisation to maintain a competitive edge. However, if there is limited trust in the data, should decisions be offloaded to an algorithm and other cutting-edge technologies?
As a result, the need to build trust in data is not diminishing - it’s growing. Poor data is often entangling entire organisations with crippling effects, preventing timely decision-making and negatively impacting on customer experience.
Experian’s recent Global Data Management research highlighted that data still maintains revered status – 85% of organisations see data as one of their most valuable assets. In addition, being data-driven is seen to give organisations a competitive advantage in several ways, notably, through improved customer experience, better insights for decision-making, and allowing more innovation and efficient practices.
1/3 of data is suspected to be inaccurate.
But the level of distrust in data remains high. According to the research, on average, almost one-third of current customer and prospect data is suspected to be inaccurate in some way. Contrast this with 98% of organisations that say having high-quality data is either extremely important or important in achieving their business objectives. These statistics highlight that organisations are entering a stand-off on the quality of their data versus the benefits of how they want to leverage it.
If ever there was a time to break down this impasse and gain the buy-in and trust of the organisation to achieve business goals, it’s now.
All organisations accept that they generate and house inaccurate data to some degree - the root cause of distrust. Our study shows the negative impact this has on organisations by wasting resources and incurring additional costs, damaging the reliability of analytics and negatively affecting the customer experience.
Reaching and maintaining 100% accuracy is somewhat unlikely, but it’s entirely possible to come close and it’s something we should all be striving for. In our experience, if trust is initially built on the data initiatives themselves, this can greatly assist in bridging the gap to building trust in the data itself.
This is why data projects that maintain a focus on driving tangible and practical business outcomes are often the ones that will succeed and be lauded across the organisation. However, those that attempt to fix all known data quality challenges will invariably fail. Business-wide data quality and governance projects often take several years to accomplish and encounter unforeseen obstacles as the target moves faster than the project can adapt to.
Data quality initiatives are easy to quantify, measure and communicate.
While these longer-term initiatives do need to take place, it is essential that stakeholders also employ practical, outcome-based approaches that identify quick wins. This could be improving data quality at an initial point of capture through a website or mobile application. These initiatives are easy to quantify, measure and communicate back to the business, acting as a catalyst to build trust and secure additional funding for the next project cycle.
In many ways, the lack of trusted data stems from an inability to drive meaningful change around data over the past few years. Although, we are starting to see this change with specialist data roles on the rise, it’s these new data practitioners that are breathing renewed life into data initiatives. This is illustrated by 84% of organisations that intend to hire data engineers, stewards and scientists in the next 12 months.
The role of the office of the chief data officer (CDO) is evolving in a very similar way to that of IT several decades earlier, where IT moved from being a support function to a central pillar of the enterprise, with centralised resources. However, it’s important that the office of the CDO learns the same lessons quickly.
Is it time to change the organisation’s view of its data?
After becoming core to the enterprise, the most successful IT teams have focused on enabling the business and putting the customer first, rather than fully owning all IT/technology initiatives. The risk is that in the drive to create a CDO identity, the CDO could lose its connection to the business.
Organisations are rapidly accelerating into an era of data democratisation, allowing business stakeholders to experience frictionless passage to the data assets they demand. They are also providing access to hands-on technology and analytical tools to interpret large volumes of data. With those changes, is this now the opportunity to change the organisation’s view of its data?
By assigning goals and metrics to improve the overall quality of the data, a broader group of stakeholders are forced into a sense of ownership and accountability that cannot be ignored. This, in turn, encourages investment into employing the right systems, controls, training, and feedback mechanisms to ensure data accuracy does not erode over time, increasing the overall trust in data.
The organisations that achieve the highest level of trust in data will be those where the office of the CDO is seen to be driving the data culture change and acting as a true partner to the business.
Trust is built on belief. Belief can be built by practical data initiatives being employed, clear visibility on the gains being made against organisation objectives, and an embedded culture of direct accountability for data quality across the organisation.
If an organisation can start building belief through taking practical and impactful steps to improve data quality, then trust in the data itself will also spread.
Clinton Hook, director of data governance, Experian