If your data and analytics capabilities are letting you down, the problem may lie with your data management foundation. To build a better data management approach, you need change in four key areas.
Technology is the most obvious place to start when trying to fix problems with data management. But there are a few other key areas that organizations need to address:
- Organization and governance
- Processes and control
- Culture and behaviors
The right changes in these areas will ensure organizations effectively and efficiently harness the full value of their data.
Data management starts with the right culture, behaviors and values
The right behaviors tend to be deeply ingrained in ‘digitally native’ businesses such as digital media agencies, which have been powered by data since their inception. They can be more challenging to embed in long established organizations with a more traditional heritage, where the role and importance of data has grown so quickly and suddenly.
To create the conditions for success, the right tone must be set from the top. This must be underpinned both by strong change management and by performance metrics and management to motivate and positively reinforce the right ways of working.
Everyone in the organization should place the quality and integrity of data at the heart of everything they do.
The right culture, behaviors and values are a vital foundation for all the other interventions below. It is crucial that the change journey starts here.
Adapt your organizational structure and develop the right governance over data
A frequent mistake is to try to hand off the data management problem to a data management team or outsourcer to ‘fix’ on behalf of the business.
In reality, this is not a problem that can be neatly packaged up and given to someone else to solve. Everyone involved in creating and sourcing data must take responsibility for its quality and integrity – and given the increasingly intrinsic nature of data, this means that most people in the organization will have some role to play. Trying to ‘give the problem away’ can undermine the sense of ownership and responsibility which is so essential to success.
However, adapting the organizational structure and deploying additional resources to support and enable the business to take on its responsibilities is crucial. Key roles may include:
- Maintaining clarity on processes, responsibilities and data management metrics
- Maintaining and overseeing the application of data architecture and data standards to facilitate data integrity and integration, as well as information security standards to protect data from unauthorized use
- Managing, deploying and ensuring consistent use of structural master data (and master data mapping, where necessary) across the business
- Ensuring that people throughout the business have the skills needed to manage data effectively.
Having the right governance in place to ensure the business holds itself to account for sustaining and continuously improving the security, quality, integration and integrity of its data assets is also key.
End-to-end data processes and controls across the business
An organization’s most important data entities are typically assembled and reused across the enterprise, rather than being the sole preserve of individual functions.
Take product data within an FMCG business. R&D, marketing, supply chain and many other functions all need to contribute data and content at various points in the process to build up a complete and accurate record for each product, which can be reused consistently and with confidence by all.
Clear, integrated processes, accountabilities and control points, which cut across functional silos and extend end-to-end, are vital. This will not only safeguard data quality and integrity – but also ensure operational execution remains fast, responsive and efficient.
Extend your technology investment to all areas of data management
If the journey starts with the right culture and behaviors, it ends with the right technology.
Technology is too often thought of as the first step or even as a panacea. It’s not. Too many businesses begin by investing in expensive data management solutions to find that they’ve only succeeded in ramping up the production and distribution of bad data. Worse still, by distributing this data from a shiny new system, they create a misplaced confidence in its quality.
When the time is right to invest in technology, it’s important not to limit its use to data integration and aggregation. Technology can play a vital role in enabling the people and process changes already mentioned above. It should be extended into areas such as process orchestration, data governance, data performance management and data quality management.
Recognize and respond in time to the data challenge and opportunity
Many organizations will need to fundamentally change their approach to managing data to benefit from its value. Some have learned the hard way that this a challenge at the heart of the business and not something which can be addressed through only technology and/or outsourcing.
Organizations which gain this understanding, and are able to respond in time, will find success in harnessing data to drive future business growth.
