Data-driven strategies will fail without investment into skills
By Jacques du Preez, CEO at Intellinexus
To build a winning data team, every organisation needs to be its own coach and nurture team members as they develop the requisite skillsets.
Without adequate investment into developing data-related skills, organisations will not realise the benefits of data-driven decision-making. What's more, they will almost certainly fail to transform their business models to deal with the ongoing uncertainty and disruption.
Bringing an effective modern data strategy to life requires a broad spectrum of skills that span data architects, developers, technologists, business strategists, data scientists, analysts and more. Think of it like a rugby team: no single player can play every role in the team, so instead you have a collection of specialists that each bring unique capabilities.
Confluence of data skills
In the past three years, however, we have seen an amalgamation of various skillsets and expertise, leading to new types of roles within data teams. For example, data analysts now have to bring ETL (extract, transform, load) skills, business analyst skills and traditional data analyst capabilities.
Similarly, data engineers have evolved into multifaceted specialists that have a range of skills so broad it used to be split between multiple roles.
This progression is a natural evolution: as data strategies mature and teams acquire new skills, related tasks are completed faster, leaving time and scope for new innovations or the realisation of additional value within the same timeframe.
The same can be seen in the technology used to enable data strategies. Building an effective data warehouse, for example, could take 10 to 12 months before value is realised. With modern tooling, agile methodologies and the benefit of extensive experience, organisations can now see value within three months. After six months, organisations could enable up to five times the capability they were able to a decade ago.
This evolution of technology, skills, knowledge and experience is contributing to a rapid deployment of capabilities and quicker realisation of business value.
However, it's not without its challenges. As the morphing of traditional data roles continues and technological progress accelerates, companies are finding it increasingly difficult to find suitably multi-talented data specialists to support their data and business transformation strategies.
Finding the best 'half-baked cake'
The truth is many of the most-wanted data-related skillsets are not yet available in the form that organisations ideally need them. Finding a multi-talented data analyst with strong ETL and business strategy capabilities is no mean feat. There are simply too few educational facilities producing these types of data professionals at the speed and scale needed.
This has led to some organisations 'poaching' talent from their competitors by offering ever-increasing salary packages, but this creates more problems than it solves. Talent retention is increasingly difficult when your best people are constantly approached by recruiters with ever-larger salary offers.
Since candidates with the perfect mix of skills ingredients are not readily available, organisations have to recruit for the best 'half-baked cake' they can find, and do the hard work of upskilling that person as quickly and effectively as they can.
Business sector needs skills mind-shift
At a training level, most formal degrees simply don't equip graduates with the broad range of skills they need to be effective players in a data-driven team. Instead, these broadening skillsets are acquired on the job, with heavy investment into continuous professional development required of the employer.
Fundamentally, the business sector needs to acknowledge that there is a skills shortage that won't be solved by waiting for young graduates to finish university. Instead, organisations need to establish robust internal training programmes that do the work of getting talented young graduates truly work-ready and able to deliver on modern data strategies.
Yes, there are no guarantees that top talent won't leave for other opportunities when they have acquired their skills. And yes, training and development can be costly. But the alternative – no skills to support business and data transformation activities, low data maturity, ineffective decision-making, lack of adaptability – poses a far greater risk to organisations' long-term success.
With the growing importance of building data-driven decision-making capabilities to help business leaders deal with uncertainty and disruption, it is safe to assume that most – if not all – organisations will require ever-increasing numbers of data specialists.
Business processes or job functions that are being automated through technology would naturally lead to some skills becoming redundant. With a robust internal training and skills development capacity, organisations could retrain and redeploy these skills back into the business to support the data strategy.
This would hold the dual benefit of greater talent retention as well as the ability to continuously match internal talent demands with a steady influx of skilled data specialists that can support the realisation of data-driven decision-making across every aspect of the business.