Developing Data-Driven Organizations - Expert Insights

It’s well established that proper data management can help demonstrate compliance, be a source of competitive advantage and reduce operating costs through operational excellence. Financial Institutions (FIs) are investing in long-term change programs often build around technological advancements to optimize management and usage of data. To become a data-driven organization, all employees working with data must be skilled and incentivized to properly manage the data during its lifecycle.
 

Incentivizing the focus on data quality

Data flows between applications and geographies without regard of organizational silos. In many FIs, the hierarchical organization model is not designed with the data lifecycle in mind. The effect is that departments using certain data (e.g. for reporting and disclosures), don’t always know where their data is originating from or who is accountable for that data. This hinders agreement and adherence to data standards and mitigation efforts at the source in case of data quality problems.

A data-driven organization has a hierarchical or virtual team structure that enables collaboration between data owners, stewards, and users across the data lifecycle and value chain. This is reinforced by each layer of the organization with strong champions on management level that recognize and prioritize data management activities. By including data management in the incentive scheme (e.g. KPIs), both individuals and teams are supported to focus on proper management of the data (e.g. resource and time allocation). Given that measuring success is an effective way of encouraging the end-to-end collaboration and continued focus on data quality.

Data capability building

The amount of data created and used by FIs is significantly increasing year over year. Data usage is growing in each department as well, ranging from HR/marketing to Front Office, Finance and Risk. The capabilities and awareness of standards among employees using data typically varies.

The result can be persistent data quality issues that start early in the value chain that only come to light towards the data usage stage. Data-driven organizations ensure that clear enterprise-wide standards and frameworks are in place and that teams handling data are trained to comply with these standards. Yearly training and development sessions on the data management solutions and company policies should be the cornerstone of employee development paths. A powerful way to foster a data-driven culture is the launch of data communities.

These communities bring together peers (e.g. data stewards) from multiple departments of the FI to follow trainings, share knowledge and best practices together. Communities can also unite stakeholders from one end-to-end data domain (e.g. mortgage data) to optimize existing processes, issues or define requirements for change initiatives. Communities help nurture a data culture by bringing together different individuals and teams to build data capabilities and optimize end-to-end collaboration.

Supporting tooling

Supporting owners, processors, and users of data with effective tooling is a key enabler of proper data management. The objective should be to enter data first-time-right, rather than focus on downstream efforts to measure, monitor data and mitigate issues.

This starts with the applications used to key-in data (e.g. front office applications) and removing as many manual steps as possible for users, enforcing users to follow standards/procedures and providing clear instructions on the meaning, relevance of each field.

To manage data throughout its lifecycle (e.g. master data, meta data, lineage, data quality) there are many powerful applications available that can do the heavy-lifting to keep track of data across the lifecycle and roll-out standards enterprise-wide.

Conclusions

The key to developing a data-driven organization is empowering data owners, processors, and users. Key enablers for this are creating a strong data culture in communities that group data stakeholders across locations, and data domains together to share knowledge and experiences.
By training stakeholders and supporting them with incentives (e.g. KPIs, targets, coaching), intuitive tooling and clear standards they will take care of the data and unleash its value for the organization.

Sparked your interest?

At Synechron we are more than happy to explain how your organization can benefit from our experience in assessing and (re)designing processes. Over the years we have helped numerous clients with the change to more resilient reporting processes and tighter data control.