The primary mission of many data and analytics leaders and chief data officers (CDOs) consists of building an effective team to establish data and analytics as a strategic discipline within their organisation. The business value is often being measured by improved business efficiency, effectiveness and innovation to drive change and digital transformation.
While in many respects data and analytics has enabled organisations to be more agile, progressive and insightful than ever before, the economic recession has swiftly taken leaders back to the early days with a reduced headcount and shortage of deployable talent. However, as the economy recovers, CDOs are likely to encounter five critical roadblocks in re-building their teams.
Changing the culture of the organisation means changing the hearts and minds of individual employees. The pandemic has forcefully done this and data and analytics leaders are the point of influence to bring reinstate a data-driven culture across the organisation.
To start, base projects around collaboration, co-operation and problem-solving for your team to re-build the trust and teamwork processes. The other business units should be engaged in an awareness programme so that data and analytics team members can give presentations, organise hackathons and, most of all, spread the word about how data and analytics can help drive business outcomes and recovery.
It’s also best to inform employees about the organisation-wide data strategy and its objectives, then ask for their support and input to give them equity in the organisation’s data progress. Leading by example is critical to re-establish the norm when it comes to how data is perceived. Showcase results - this way the enterprise will see some real-life examples of how data and analytics has created value and has affected daily operations.
The key message to communicate is that data and analytics is not a technology implementation - it is a change management initiative.
The phrase “data is an asset” is more common today than ever before. However, data and analytics processes are often not set up to monetise the enterprise’s information assets. Monetisation is often held back by an internal and IT-focused approach to the data and analytics discipline, and by existing business silos that are responsible for monetisation.
This results in a disconnect between the data and analytics team and the much-needed business outcomes. This manifests itself in not being able to then secure the desired funding and resources for data and analytics programs because leaders are asked to show the business value of data and analytics to their organisation and this can often fall short in the expectations of the board.
Explore a more experimental, prototype-first mindset with the creation of a sandbox to allow domain leaders and their cross-functional teams to play around. In this environment, there is a lot of freedom for leaders to integrate data, select a particular tool and build their own analytics.
However, sandbox products need to be treated as prototype content - they are not fit for production just yet. They need an additional process to make them into more robust solutions. Not all prototypes will make it to production; some need to remain as prototypes. They might serve some quick demand, but most of all they can be used by teams to discover the value of data and analytics and reveal which additional capabilities are needed.
The CDO’s desire to establish a data-driven culture is often hindered by poor data literacy across the organisation even without the interference of outside economic forces. Without data-literate employees across the business, business leaders will remain unclear about what data it has, what the data could be used for and the quality of the data. As a result, organisations will fail to identify potential business opportunities.
One of the first things to do is to collaborate with HR and line-of-business leaders to assess skills requirements. Then start with a pilot for an up-skilling roadmap developed for the group of stakeholders who already have enthusiasm and appetite for data and analytics and who recognise that improving data literacy is a vital factor for success.
Ideally, choose to run the pilot in a business area where there is high likelihood of achieving measurable business outcomes. Then use it as a case study to educate the organisation on what it means for business recovery opportunities.
Identify or survey the current available skills, roles and competencies within your organisation and match those against the business recovery demand that comes from the various business units. In this way, the deficit in data and analytics skills becomes clear and allows you to up-skill or re-skill talent, using external support where needed.
Through 2023, data scientists and analysts will lose 60% to 70% of their productive time to activities like finding, preparing, integrating and sharing datasets. Automating hands-on support will be key – with the limited team you do have, try to implement more self-service capabilities to reduce the reliance on the data and analytics team which stretches it too thin. This will also enable the enterprise to start working on some of the initiatives with a quicker time to value, while at the same time get a better understanding of the needed skills and capabilities.
Another way to narrow the skills gap is by employing innovative ways to source different roles and skills. One example is by working with academia through partnerships and another is by hiring academically specialised interns. The latter is a simple lever to pull, but make sure to partner interns with business domain experts, otherwise this approach will fail.
As the economy recovers and business is more stable, a big challenge will be realigning focus to the initiatives that are most important. Do you just resume ambitious initiatives that were paused because of the pandemic or begin new projects from scratch based on today’s need?
Looking at the current state of data, people, process and technology across your enterprise can give guidance toward the next level. This can be a wake-up call or even a discussion piece during a recovery workshop with the leaders of the various business units.
However, whatever you decide, don’t spend too much time designing new processes, governance structures or data architectures. The agility forced on to your team during the pandemic may have been foreign, but it does not need to be abandoned completely. Through iterated business-driven prototyping and discovery, new value will be created.
Jorgen Heizenberg, senior research director, Gartner