Structuring your strategy on sound data

Published: 06 June 2018


 “Quality data is good business,” says Stuart Pearce, managing director of TD Global, “and is now the currency of global organisations. However, without a strategy to ensure both the quality and democratisation of your data, you’re sitting in a rocking chair. Moving, but not going anywhere.”

While “CDO” – chief data officer – has become a fixture in the C-suite, companies around the globe are still not entirely on track when it comes to using the data to make business decisions or giving access to those who should be making decisions. “According to Gartner figures published in Harvard Business Review in mid-2017, cross-industry studies found that around 70% of employees have access to data they should not, and analysts spend 80% of their time on discovering and preparing data,” Pearce says.

This scenario makes for easy data breaches and data technology that can’t stand up to the demands required by businesses, he adds. So, how does an organisation ensure quality, robust data that adds value?

Firstly,” Pearce asserts, “the data management team, often headed by a CDO, must clarify precisely what they want their data to achieve, and use that as a base for a strategic data management plan.

“This will enable organisations to allocate their resources for maximum efficiency, while structuring their data-management activities to support their overall strategy. All the while, the team must also remember that the build will give access to a number of different types of employees and ensure all are able to navigate their way toward answers or solutions for clients.”


Legacy data and silos

Once clarity of purpose is achieved, the big clean-up begins. “Legacy data that continues to sit in silos needs to be cleaned and updated for use in today’s market,” says Pearce, noting that the importance of this part of the process cannot be overstated. “If one cog in the centre of a massive machine doesn’t function, the machine ceases to function.”

Therefore, the CDO, with the team’s buy-in, must determine which of the existing data sets are valuable enough to migrate, and which can be left out of the new structure. “Anything that is not fit-for-purpose will not add value,” Pearce posits, “so the data team must constantly bear the result in mind.”

By starting with data hygiene and then migration of clean data, Pearce believes that the team can be assured that the rest of the structure is built on a solid foundation, making the path to data as a currency a successful one.

“Note, though, that TD Global recommends building contingency time into any deadline in case of errors during testing, and a project management system that is accessible to all may require broader access across the data team during the build.”