Does your organisation fully appreciate how important data capability is to success?
Does it appreciate the need for all employees to have a minimum level of data-related competency?
Data is no longer a specialist skill; it is a core business capability.
Many organisations understand that data is the foundation on which their processes operate. However, translating this awareness into the realisation that everyone in the organisation needs the ability to directly and effectively create and utilise this foundation, is not as greatly appreciated.
Key considerations for your Data Foundation
When looking at the state of the data and its ability to support future initiatives, things to consider are:
Data Governance - have you implemented a sustainable governance function? Are Data Owners and Data Stewards fulfilling these roles? Are meaningful Data Policies in place? Do you have transparent, ethical usage of data? - Data Governance needs to be integrated into daily operations.
Data Quality - do you have standardised definitions and consistent use of terminology across the organisation? Is the quality of critical data continuously measured? Are root causes addressed, not just symptoms? - trusted data is essential.
Data Platforms - have you transitioned to cloud data platforms, consolidated data warehouses and lakes, improved integration, enabled real-time analytics? - AI is driving the need to be scalable.
Data Analytics - as analytics become embedded in daily operations and self-service BI expands, decision-making is shifting from technical teams to business users - Data Analytics must become part of everyday business activity.
Data Management - organisations are extending data capabilities and improving Data Management Maturity across the organisation, enabling better collaboration across business units when it comes to data -Data Management Maturity is a key enabler.
The traditional model – Data Teams and Data Specialists
Traditionally businesses have built their data capability through dedicated data specialists and data departments. Data Capturers, Business Intelligence/Data Warehouse teams, maybe a Records Management or a Data Quality / Data Governance project. These were the people responsible for the data, while the rest of the organisation got on with marketing, sales, or customer service etc.
As technology evolved, processes and decision-making have become increasingly dependent on the underlying data, and the number of data roles and data teams across the organisation has grown accordingly. Companies have introduced roles such as Chief Information Officers or Chief Data Officers, and they have expanded functions, with multiple teams for Data Governance, Metadata, Data Quality, BI & Data Warehousing, Data Engineering or Master Data Management.
Things are changing again
As organisations turn their attention to Artificial Intelligence (AI), executives have realised that despite this growth, certain challenges remain:
- Analytics are not yet business-led
- Quality remains inconsistent
- Similar reports often produce conflicting results
- Compliance and ethics continue to pose challenges for governance frameworks.
In spite of having these dedicated data teams in place, gaps remain.
Many businesses are lacking a solid data competency on which to build. To enable transformation readiness, the development of data-related skills development for all, is required.
While Data Professionals must continue to be equipped with the specialised expertise, they need to support the transition; organisations must also ensure that all employees achieve a baseline of data competency, to work effectively in the changing environment.
Today, everyone works with data, understanding it, interpreting information, generating insights, and creating reports. Data underpins virtually every business activity, making elementary data-skills essential for all. In addition to the obvious AI-specific skills to be developed, Data Literacy for the entire workforce should be addressed.
Your Data-Skills Development Strategy needs to include plans to educate those who traditionally, have not been deeply involved with data. This is where significant, often untapped opportunity exists.
The current emphasis is on technology, and its deployment usually sits centre stage. However, technology alone cannot create value. Institutions need to focus on the deployment of the technology, and the supporting elements of people and process.
For successful transformation, all aspects of change should receive attention. Many organisations have invested heavily in data platforms and tools, but the gap lies in people’s ability to use them effectively.
Organisations must develop new competencies, to maximise their use of the emerging technology.
All staff need data skills - build a Data-Literate Culture
Whether communicating their findings, or interpreting information received, data proficiency significantly influences how well people can perform.
An elementary set of competencies that enables the entire workforce to work effectively with data - understanding it, using it efficiently and communicating clearly - can positively or negatively affect your business performance.
Everyone in the organisation now deals with data, not just the data specialists. You need a data-literate workforce, where individuals:
- understand data,
- use it effectively,
- recognise its potential,
- value its impact.
Ensure that your data professionals have the advanced skills required for their specific roles, while also ensuring that all their colleagues are data-literate, and can work with real-world data, interpret it, analyse it, and translate it into clear actions, as well as knowing how to contribute positively to the quality of the organisations’ information.
You cannot become AI-enabled without first becoming data-literate. Every employee must be able interpret the data they are using, produce meaningful outputs derived from the data, and contribute to its quality. They need to do more with data now than they used to.
If all employees work competently with data, they will be able to determine:
- whether the data is accurate and trustworthy
- if you have the required metadata and lineage
- whether the governance practices are adequate
- if you will be able to scale safely
- whether the data is fit for AI use.
Organisations should focus on strengthening Data Culture, Data Centricity, and Data Management Maturity. By improving maturity, you will unlock greater value to benefit all your initiatives.
If the organisation’s overall Data Competency and Data Management Maturity are strong, you will be significantly better positioned to succeed with AI initiatives.
