8月 2021 | Data Quality |

In the third and final article looking at Experian’s 2021 Global Data Management Research Report, we explore what the future of data management looks like and how to build a robust and future-proofed data management operation.

 

Better data management powering operational resilience

 

We discussed previously how data is progressively being seen as more of a strategic asset. This is no surprise as sixty three percent of organisations surveyed predicted that data management initiatives would become more urgent over the next six months. One of the key reasons for this rise in urgency is organisations wanting to be more resilient – in their operations and their decision making. Nine out of ten businesses are focused on improving data management resilience to at least some degree over the next year.

 

By focussing on the robustness of their data and data-related initiatives, organisations can then proactively tackle three core operational areas:

  1. Deeper customer insight – React quicker to rapidly shifting consumer behaviours
  2. Collaborating for societal good – Leveraging data, talent and resources to benefit society at large
  3. Investing in talent, skills and tools – Hiring the right people and empowering them with technology to drive data advantage

 

Organisations recognise that investing in data management today will better help them be more resilient and cope with unexpected events in the future.

 

Key data-related priorities for the year ahead

 

Over half of the organisations surveyed stated they are looking to improve data quality. Given the lack of trust in their data that many organisations cited in this study, it’s encouraging to see this as the top area for data management investment.

 

Implementing or improving data governance is another key area of focus. This makes sense given the constantly changing regulatory landscape and proliferation of self-service data management throughout organisations. Organisations need to ensure their data processes are governed and robust.

 

Finally, we are seeing that many organisations are looking to automate their data management operations, leveraging machine learning to improve accuracy and reduce the need for manual intervention.

 

The priority areas identified are not quick wins but strategic pillars or advanced data management. Reaching a state of data management maturity is also heavily reliant on who you hire, the technology you implement and how you build out your operations.

 

Improving data management maturity

 

For organisations lower down the data maturity curve there is a lot to plan for with often limited resources. Below we discuss some of the key areas to think about when building a high performance data management operation.

  1. People

    Our research shows eighty five percent of organisations are hiring data roles in the next six months. This is a clear indicator of the focus data management is getting as a strategic priority. One role in particular is an extremely critical hire for organisations: The Chief Data Officer.

     

    Over the past several years, we have watched the journey of the Chief Data Officer (CDO) very closely. This role was brought into the business to put more structure around the usage of data and promote collaboration across various departments.

     

    By increasing the visibility and importance of data across the organisation, a new issue has arisen – data literacy. Seventy four percent or organisations surveyed said data literacy is a core competence that all employees need to have in the next five years. Additionally, sixty two percent say a lack of basic data literacy skills is impacting the value they get from their investment in data and technology.

     

  2. Technology

    Technology has a critical role to play when it comes to modernising data management practices. Our research found that eighty five percent say sourcing more technology for staff is a top priority. However, the right technology needs to be leveraged to ensure it is effective.

     

    Technology must be intuitive, so business users can utilise it, it must be agile, so those same users get the answers they need quickly, and it should be governed, so the business protects itself from a regulatory and compliance perspective.

     

    Our data management and data quality tool, Aperture Data Studio, let’s organisations tackle all those things. Data profiling and discovery become easy tasks, instantly uncovering relationships between siloed data assets and letting business users get the answers they want. Data quality becomes an automated operation with easily configurable rules, advanced alerts and dashboards.

     

  3. Agile data operations

    Our research has shown that organisations are struggling with a lack of agility when it comes to their data. Many were not able to quickly adapt data practices to the changing needs of their organisation as the pandemic took hold.

     

    By adopting an agile data operation, organisations can shorten development cycles, increase deployment frequency, and create more dependable releases of data pipelines, in close alignment with business objectives.

     

    In the survey, we asked respondents how they were looking to bring agility to their data initiatives moving forward. Many are focused on introducing more user-friendly tooling, while others are looking to gain more feedback from internal stakeholders, hire more data staff, and improve governance procedures.

 

Agility, talent and technology

 

It’s clear that the pandemic has impacted organisations’ operational capabilities significantly. Our research has shown that amongst a sea of shifting consumer behaviour, organisations have identified that data management must be a strategic focus. The key principles remain unchanged. Hire the right people, equip them with the right tools and empower them with agile processes in order to be effective. Get these right and organisations will take a giant leap forward in being able to deal with unexpected events in the future.