Across an organisation it can have many requirements, for example, it can predict which candidate will be the best fit for a new job opening or which suppliers are most suited for a particular product line of parts.
How can you improve your data maturity?
There are many approaches organisations may decide to take in order to increase their data’s maturity. The most important aspect to consider when looking at the maturity of your data is data management.
In short, the better your data management is, the better your data maturity will be.
However, simply improving your data management is not an easy task, especially when working within larger corporations. It’s a process that needs to be broken down into smaller pieces, that add to the bigger picture. You can improve various aspects of your data management by adopting some of these common processes:
- Define a data strategy – Develop a clear data strategy which aligns with the organisation's goals which include how an organisation intends to collect, manage, analyse and utilise Data. This also includes defining its approach to Data Governance, Data Architecture, Data Quality, Security, Data Privacy and Data Analytics.
- Set clear objectives and goals – Define specific and measurable objectives for improving data maturity. Important for organisations to benchmark current maturity levels and acknowledge/action areas of improvement as the data maturity level progresses.
- Invest in technology – Evaluation and investment in modern data management technologies that support data storage, processing and analysis. This can include Data Warehouses, Data Lakes and advanced analytics tools. It is crucial to continuously invest in technology ensuring a competitive edge and long-term value for the organisation.
- Monitor and measure progress – Establish KPIs and regularly monitor progress in terms of the impact of data management initiatives. A key activity that all organisations should be doing is to know where the organisation has come from in terms of data maturity, and its current level and to know the requirements to get to this point.
- Document best practices – Ensure best practices are well documented across the business, this is very important as this provides the footprint for an organisation to ensure its data maturity has long-term sustainability.
Quote from Stephen Moffit at We Are Atmosphere:
"In order to take advantage of the potential value of AI and analytics, businesses need a good level of data maturity. This means:
- Robust data governance and management to ensure the quality of the data being used
- Data intelligence across the business to enable everyone to understand, question and interpret the outcomes from AI and data analytical tools
- A culture that is built around the sensible use of data to achieve value and recognise opportunities in changing markets."
The key benefits of ensuring data maturity
Data maturity brings several key benefits to organisations as they advance their abilities to manage and leverage data effectively. Some key advantages as explained below:
- Informed decision-making - Mature data management practices enable organisations to access accurate, timely and relevant data. This ensures decision-makers make informed and strategic decisions based on data-driven insights rather than guesswork or hunches.
- Competitive advantage - Data maturity enables organisations to leverage their datasets more effectively gaining further insights into market trends, consumer behaviours and competitor strategies. This enables an organisation to adapt and innovate faster and gain that competitive edge.
- Innovation and adaptability - Data maturity naturally provides an organisation with a mindset of innovation and growth ambitions. It encourages experimentation, exploration and data-driven problem-solving across the organisation.
- Cost savings – A data-mature environment ensures an organisation optimises its data infrastructure, reduces data redundancy and eliminates inefficiencies resulting in cost savings
- Long-Term Sustainability - By investing in data maturity organisations lay a solid foundation for long-term success and sustainability.
Final thoughts
Overall data maturity is a critical aspect of an organisation's ability to harness the full potential of its data assets.
In summary, achieving high data maturity is a complex process that involves multiple departments, processes and technologies to come together with a common understanding and drive for business success.
About the Author: Daniel Neaves
Daniel is a Senior Consultant within the Tech Specialisms practice focusing on the data market at Harvey Nash.
With over 7 years of experience within the data domain, Daniel’s knowledge and expertise cover a broad space within the UK and German tech permanent markets.
If you would like assistance in bringing onboard data experts who can significantly enhance your data maturity or would like to find out more about Dan, please get in touch at daniel.neaves@harveynash.com or visit his consultant profile here.
