Demand is so high, even PhD candidates are dropping out to cash in.
Everyone from HR up to the boardroom keeps referring to the data and analytics industry’s infamous skills shortage.
The demand for talented technical individuals to staff up a data team is nothing new - but now companies aren’t even waiting for the highest-skilled talent to complete their PhDs. A recent survey found that actually only one in four data scientists achieve this academic qualification, with many entering employment in commercial organisations early to monetise their skills.
Some data practitioners have also been swayed into thinking the solution lies in investing more budget into technology as opposed to nurturing their team’s skills to solve the problem. Machine learning and artificial intelligence are this year’s buzzwords with many future-gazers viewing them as the answer to all our data problems.
Yet, as the digital transformation across industries continues to develop, it is the human dimension of this revolution which has been revealed as the key to unlocking value and ensuring sustainability of these changes.
Soft skills - not high tech - hold the key
Soft skills are the critical dimension that advances a data team from number crunching and trend spotting to delivering real step-change insights and value for the organisation. Communicating to stakeholders and getting buy-in will accelerate a transformation faster than just implementing a new system.
Chief data officer of Sainsbury’s, Andrew Day, is a huge advocate for developing the soft skills of his 50-strong team. He commented in a recent chat with DataIQ: “Cohesive, rigorous and ongoing soft skills training for a data team is a new concept, but one which is crucially important to our industry. Learning programmes should focus on developing the skills that help a team transform from just analysing and reporting to storytelling the ‘so what’ of data - revealing invaluable business insight that can revolutionise how organisations operate.”
Day continued, “we’ve had outstanding internal feedback after subscribing my team to an ongoing development programme - both at a functional level, through the value they have gotten out of the training, and at a strategic level, via the various peer-to-peer networking events.”
There is nothing “soft” or even “easy” about the ability to communicate effectively and problem solve in business. These are vital skills required by every good decision-making professional. As it is now data that drives decisions in leading organisations, there is no excuse for leaving your data team without the skills required to communicate its value.
Our 2017 research revealed nearly half of the organisations found that the lack of good candidates was creating a barrier for their business. With so many companies fishing in the same recruitment pool, it is no surprise that all-round talent is so hard to come by alongside the soaring salaries which accompany a skills shortage.
So, how are these organisations intending to fill the gap?
DataIQ found that over half of the companies plan to upskill existing staff as opposed to recruiting in new blood. As well as meeting needs in the short-term, this saves a company time and recruitment efforts – provided it changes its culture and puts the right resources in place.
Therefore, instead of spending time and money hunting for an elusive data science “unicorn”, why not improve the performance of your existing data and analytics stable by enhancing its skills? Organisations which are reaching maturity in data and analytics practices - and even those which consider themselves as already advanced - still recognise the value of continuously training their staff to maintain their lead.
And it’s not just CDOs who are noticing the need to give their data teams a soft skills boost – employees on the ground have expressed their concerns over the lack of these skills within the industry.
Data Scientist at Qriously, Emma Walker, told DataIQ in a recent interview, “as data science team outputs become increasingly based on machine learning or deep learning techniques, the ability to distil the vital pieces of information to stakeholders becomes more complex. It is very easy to answer a question with an equation or a graph, but to those not as mathematically inclined, that is like speaking a different language. We need to move away from the perception that soft skills are optional or less important.”
Walker continued, “I see data scientists as filling a role that enables everyone to understand and exploit data. This means we need to be data ‘translators’ for our colleagues. You can't learn how to do this from a textbook, it takes time and practice, and sometimes external coaching, to frame the material in the best way for your audience. Understanding data shouldn't be the preserve of the data scientists, but it should be our job to lead the way for everyone else.”
Walker’s modification of the Drew Conway diagram
Is it worth the investment?
According to a YouGov poll, 97% of UK employers believe soft skills are important to their current business success and over 50% say skills like communication and teamwork are more important than traditional academic results. If you don’t nurture these skills, the knock-on effect is that individuals and organisations experience a loss of productivity, profitability and competitiveness.
“Best in class data teams require a combination of great leadership, technical investment and talent development. Ultimately, transformation starts and ends with the people - technology is merely an enabler,” advises Caroline Florence, director of Insights Narrator. “Talent development is not just about keeping technical skills up to date - it also requires a focus on building problem-solving and communication capabilities as well as commercial acumen. That way great analytics will help solve the right problem and be shared, understood and used throughout the business to inform actions and decision making.”
Providing data and analytics with soft skills can have an immediate impact on their performance - and therefore their value to the business
According to Florence: “In my experience, providing data teams with clear frameworks in a training environment makes them feel more comfortable with change. Using the training to build confidence in applying to real-world scenarios makes them willing to push the boundaries a little bit further. Providing some automatic quick wins that they can apply as soon as they get back to their desk makes it feel achievable in practice and provides the initial momentum needed to kick start the transformation process.”
However, there is an obvious problem here. Soft skills development and staff training cost a company time, finances, and resources – and some senior management may not initially see training-up a team’s soft skills as a necessary expenditure.
As Walker comments: “When it comes to training, there are hundreds of data science blogs where people play with the newest tools to be released and provide code examples or even full tutorials for free. My opinion is that, if you have a limited budget for external training, suggest your employees work on those skills that cannot be learned online and require other people to practice with.”
Achieve your data and analytics transformation in 4 steps
With so many other exciting opportunities around for budgets to be spent on, how you can convince your boss that this is one investment that they absolutely need to make? These 4 steps will help you to build your business case for soft skills investment.
1. Identify the specific areas for improvement within your data function
It is unlikely that you will get buy-in for absolutely everything you want straight away. Only 32% of organisations we surveyed intend to increase their expenditure for data and analytics significantly in 2017. So prioritise. Use capability assessment tools to help identify which areas need the most attention and then summarise how this investment will improve the skills needed to get your team to the next level.
2. Compare your soft skills gap within the industry and benchmark against your competition
An incredibly powerful tool for building a business case is understanding where you stand compared to the wider market place.
After taking the time to run a capability assessment of your team’s skills, benchmark them against the industry and, more crucially, your competition. This will help you to justify how much – or little – investment is needed to shift your capabilities beyond that of your competitors.
3. Talk to the wider business
Data and analytics functions should serve many different areas of the organisation and understanding how the different stakeholders view your team may deliver some insight that a capability assessment alone can’t. Did they find your team easy to work with? Did they take the time to truly appreciate and understand the problem? Were stakeholders kept informed throughout the project?
These are commonly-cited challenges of working with data and analytics teams which frustrate stakeholders and are addressable through soft skills development, removing barriers to the positive perception of data and analytics as a function.
4. Identify a soft skills development programme for your team and individuals
Think of the ultimate end goal you want to achieve with this investment. Every data team is different and every individual within that team draws upon different strengths and suffers from different weaknesses. You know your team - what additional soft skills does it require to develop at an individual and team level?
Explore different workshops and programmes that will address your team’s specific needs and present a selection to your boss, ranging from the ideal choice to the most cost effective. Everyone likes to have options, so don’t go into the meeting with just one solution.
Admittedly, alongside the demands of your already time intensive job, these 4 steps may seem like a daunting task.
A practical place to start is here - a capability assessment of your data team
There are a range of options and tools available that can do the groundwork for you, such as our free DataIQ Leaders Capability Assessment, which evaluates your team’s core capabilities - from leadership to technology skills - across key data functions such as customer analytics and data science.
This allows you to get a high-level view of how strong your data and analytics function is, where its high-risk areas lie, and how you compare against your sector and the wider industry. This generates a substantial section of your business case.
To find out more about our DataIQ Leaders Capability Assessment and to assess your team’s capabilities for free, click here.