Where to start a data academy: Personas and skills matrices
A common starting point for organisations embarking on this journey involves defining the various personas and roles within the company. Identifying which roles require specific data skills is crucial. Involving learning and development teams early in the process is beneficial, as their engagement ensures sustained participation in the programme.
Building personas aligned with a data literacy framework has proved helpful for some organisations. While others emphasised the importance of recognising that not every employee needs to undergo the academy, a skills matrix where individuals self-assess can aid in targeted training.
Budget constraints may lead some organisations to focus initially on creating a small centre of excellence within the analytical community. This approach allows for concentrated skill development, with some stressing the importance of emphasising soft skills to mould individuals into well-rounded business analysts.
Building data capabilities: Apprentices, graduates, or both?
The approach to building data capabilities varies, with some companies considering apprenticeships as the most viable option. However, the maturity of the organisation plays a pivotal role in the success of apprenticeship programmes. For others, the apprenticeship route was considered too time consuming, requiring too much management oversight, so they opted for hiring graduates and rotating them through various departments. In both cases, participants emphasised the importance of being clear at the start which functions would be best able to support and manage these individuals.
Whatever the level of new joiner, providing a clear career path from analyst to analyst lead is crucial for retaining and developing talent within the data team.
Where time pressures play a part, some DataIQ members collaborated with partner organisations to help identify and attract the right talent into the business.
Tips and tricks for embedding a data academy: More a mindset than a checklist.
For those who would have started their journey two or three years ago, the success of a data academy lies not just in the technical aspects but in cultivating a mindset conducive to data-driven decision-making.
For all members, the level of soft skills and the ability to tell stories with data was a key component of any successful data academy and many talked about the importance of finding supporters and general advocates and making as much use of them as possible. This included ensuring the Leadership team understands the importance of data and the need to think differently.
For some, embedding the programme was helped by being in the same physical space wherever possible – and building strong relationships with both with HR, learning and development and key business advocates. Some suggested that it was helpful to avoid using the term data literacy and reference being more data savvy as business teams seemed more receptive to this term.
Using gamification was suggested as a way of embedding new ideas but those who had used this route stressed the importance of ensuring the simulation had to link to a business situation.
How long to embed a data academy and ensure it is successful?
The timeline for embedding a data academy varies, with some organisations having commenced their journey up to three years ago. Tracking uptake, engagement levels and the importance of soft skills are critical metrics for success. Others cited measures such as feedback from the courses, volume of colleagues wanting to take up training, dwell time on content and the percentage of those who had attended courses versus the addressable audience.
Business success measures were also mentioned. A successful data academy should be measured by improved decision-making and its impact on overall business success. Measures included business functions being better equipped to understand various reports, the percentage of transformation projects leveraging data and the coverage of C-level sponsorship of data projects.
In conclusion, building and embedding a data academy is a strategic imperative for many organisations navigating the digital landscape. The path to success involves a thoughtful approach to skill development, engagement and ongoing measurement of impact. It is a journey that requires commitment, adaptability and a clear vision of the transformative role data literacy plays in organisational success.
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