The importance of data education
The importance of data education
For financial services firms, the rise of data is creating significant opportunities. But without proper integration of data best practices, the benefits could go to waste. As we move into a post-COVID-19 mentality it is clear that in order to reduce costs and increase efficiency data and AI will need to come to the fore to help banks and other financial institutions find a route back to value.
Yet there is often a capability gap within organisations which often inhibits the ability for data and AI capacity to scale beyond the Proof of Concept stage and the Chief Data Office.
That’s why it’s vital for organisations to integrate data practises into their workstreams in an ordered manner. Education must be a core part of this process as, without full understanding and buy-in from all stakeholders, an organisation will struggle to get the most out of its data.
But what do we mean by data education? And how can your organisation put it into action?
Understanding data maturity
An organisation’s data maturity is obviously a key factor in determining the levels of granularity and the types of data programmes that are implemented. But the same is true of data education. There needs to be an understanding of the audience’s data capability before education and training material are prepared.
Determining the audience’s level of knowledge beforehand will allow for a better programme of data education to be created. An immersive programme is required for a data-informed c-suite should look different from a ‘data 101-type’ programme for a new intake of graduates
Data education can, therefore, be tiered and targeted for the particular audience. For instance, for beginners, data literacy and an understanding of terminology are critical, especially for less mature firms.
Data can be a complex subject, and it can seem intimidating. With this in mind, it should be determined that all stakeholders be educated about the basics and an organisation must learn everyone’s proficiency before educating their workforce.
If an organisation is hoping to undertake company-wide data training then a maturity assessment such as the Data Management Capability Assessment Model can be an effective way of measuring current capability to ensure training material is written at a level that is right for the audience in question. You can read more about DCAM on our blog.
Once the level of the audience is established, the more in-depth task of dedicated data training creation can begin.
It’s also important that a root-and-branch study is carried out to articulate what data means to the organisation. This provides a sense of purpose, which will be needed to guide and motivate all stakeholders undertaking the education programme. A sense of purpose will sell the benefits of data to everyone, even those who aren’t data experts or practitioners.
The key here is to make sure that everyone feels secure and enabled by data. This means going beyond handing out a few data battle cards or laying on a few optional seminars. As with all forms of education, unless it’s comprehensive, organisation-wide and accessible, any benefits will only be felt for a short period of time and will have little impact. This is where quality data education and regular assessments of workforce data maturity can help to develop a positive organisational data culture. We advocate creating a ‘data academy’ approach whereby individuals can easily find materials which are pertinent and relevant for their role and their necessary level of personal data maturity aligned to their role.
Differences are to be expected
Of course, data education programmes will vary from organisation to organisation as they depend on how mature they are as a data organisation. We will explore how to build out the specifics of data education for a variety of different data maturities in a coming post on our blog.
However, regardless of their maturing, every firm needs an immersive, multi-faceted data education platform that benefits all stakeholder, in their separate data roles. Education can be a tool to raise awareness of data as well as clarify theory. This means that programmes should be comprehensive and flexible, designed to benefit novices as well as experts.
To build an approach like this, an organisation must use a wide variety of tools and resources. These can include remote training, online resources, immersive days, battle cards and guides, too. It is important to have a vibrant mix of different resources, both on and off-line, that inspire and inform your people. Siloed e-learning alone isn’t enough to build long-lasting positive data behaviours.
Real-world simulations are also a good way to invoke different kinds of learning and enforce good data behaviours. Hackathons, data emersion days, timed team challengers and the like can serve as ‘lab-style’ learning environments that can replicate day to day activities. These can bring the theory to life in a safe environment and act as a strong and reinforced way of learning.
Quality buy-in from senior stakeholders also mustn’t be discounted. Innovative and engaging data education programmes such as immersive data days can help to demonstrate the business value of investing in your organisation’s data capability, thus unlocking funding and securing vital senior stakeholder support.
Education doesn’t stop
Just as an organisation needs to create a data policy that is agile and responsive to new inputs, an educational programme must be responsive, too. There’s no point building a programme that suits the data landscape of 2020 only to find that in 12 months it’s no longer fit for purpose – not least of all in a crisis agenda environment.
Education should be ongoing and the resources engaging so that stakeholders don’t feel like their efforts are being wasted. In any form of education, the fastest way to make someone fall out of love with a programme is to produce boring materials. That’s why it’s important that a programme is produced that truly resonates with all participants.
For this reason, education boils down to purpose. Without a clear reason why a company is choosing to embark on a programme of data education, the programme won’t be a success. Aligned to purpose is also measurability –a data training platform also needs to prove its value, through carefully designed metrics which demonstrates the success of the training. Measurement, together with a clear purpose and an engaging programme, can help to educate all employees and help them and your organisation get the most out of their data.
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We’ll be setting out in more detail how your organisation, whatever its data maturity, can build out a data education programme in the coming weeks on the blog.
We have deep experience delivering these programmes for our clients – and if you’d like to find out how we might be able to build one for you and your team, please get in touch.