For the second blog in this series, which was originally sourced from my white paper on common challenges faced by data and analytics leaders, we dive into the challenge of people resourcing. While the figures here are based on the Australian market, the core challenges and solutions are still applicable for companies across the globe.

The Problem

Finding and maintaining quality talent for data and analytics is difficult. Each country has their own unique considerations, but here in Australia we’ve got quite a few. First, we’re a very big island with a very small population very far away from everyone else. Our locally grown data talent supply is far short of business demand. We are heavily dependent on overseas talent. COVID closed our borders and created a massive backlog.

Talent shortage is true everywhere, not just Australia. The International Money Fund Predicts that by 2030, there will be a shortage of 85 million technical workers. The compounding effect is that salaries for data roles are increasing at a disproportionate rate. Immediately following COVID’s worst periods, the Great Resignation pushed salaries for data workers up by +30% to +40% in the span of a couple of quarters.

Those numbers have thankfully stabilised, but the effect remains. Quality data talent costs more today than ever. Also, according to the IMF, that shortage of technical workers represents $8.5 trillion USD in lost annual revenue.

What’s your company’s share in that loss?

Another aspect to this problem is that the longevity of tools is growing shorter. The rate at which data technology and AI is evolving means that there are new players entering the market at a higher rate.

Just think about the difference in the feature set of the tools that you’re currently using. Think of Power BI in 2020 vs. Power BI today adding Copilot plus Fabric. Or, consider Snowflake yesterday vs. Snowflake today with Snowpark, Cortex, Document AI, data apps, etc.

Different tools require different skills, certifications and expertise. Having mastery in data cubes, for instance, might be as valuable as being a steam engine mechanic. The times they are a-changing.

The Solution

There are basically three solutions here: add, advance and/or augment.

Let me explain. You can add new team members. You can advance the skills of current team members to make them more valuable and fill new roles. You can augment your team with contractors, staffing or consultants. Or you can do some combination of the three.

So, which should you do?

Add

Finding new team members to join the organisation whether on a max term contract or an unlimited presents a number of challenges. First, the global economic conditions mean most organisations are avoiding adding opex expenses, like employee salaries. In countries with strong labour rights like Australia, downsizing in response to tighter revenues can be restrictive.

My recommendation is to look for the proverbial unicorn at the senior level. Don’t settle as much as you can with the hiring budget available. You want someone with strong technical experience, a proven ability to learn, great communication skills and a dedication to hard work. Whether or not they have specific certifications …in this tech or that platform matters less. You’re hiring pattern, a trajectory of success, that solves problems. That’s the best investment you can make.

And most unicorns are all about how passionate they are about the work. Money is rarely the most important thing. If it is, you probably don’t have a unicorn but a mercenary. For exceptionally talented individuals there are other ways to incentivize them – autonomy, new tools, perks like working from home, community, culture and the like. Take a look at what you’re offering outside of just monetary compensation and round out the reward for joining your team to make it the most attractive to your targeted resource.

This is what we try to do at InterWorks with every role. Our hiring philosophy is one of the things that really differentiates us, as well as makes our recruiting cycles so prolonged sometimes. If you’ve got great leaders, then the carryon affect to the middle and junior ranks is profound. This is how you build a culture of excellence.

Advance

The cheapest way to grow your human resource capabilities is with the talent you’ve already got. Using a recruiter to find a new team member costs on average another +25% of the annual salary, for instance. Imagine you spent that money instead on upskilling four or five of your existing team. They are known quantities that are already embedded in your business and processes.

With a self-sustaining data culture, you’ve got an entire community of enterprising, self-taught data enthusiasts. These are the prime candidates to bring into a data or analytics role with proper enablement and training. The tools of today have invested so much money into simplifying and streamlining the learning curve and the UI/UX. Mastering data and analytics tools has never been easier. As generative AI is incorporated into the interface more and more, the barriers will drop even further.

Advancement of existing talent is a must-have for every organisation. Define your user cohorts as per your data governance policy, document their responsibilities and goals, then build an enablement strategy to empower them to achieve them. As you find the outliers within each cohort that are eager and capable of doing more, promote them to the next most technical cohort. Reward your community for their personal investment in data.

Augment

There are projects that require a lot of hands, a lot of effort and expertise. These are things like standing up your data warehouse or implementing an enterprise data governance strategy. Afterwards, you are in sustain and expansion mode. Typically, you’ll need fewer resources here than during your foundational kick-off.

Building a pool of consultants and/or contractors gives you that elasticity to grow and contract as needed, project by project. It also does not incur the operating expense burden of a new hire. As a consultant, in our world, there are two basic models for augmentation: staffing and consulting.

Staffing: You’ve sent out the bat signal and now you have 20 new graduates on day rates sitting in your office waiting to be told what to do. You’ve bought additional time by people with a foundational understanding of how to do things, but less so of what needs to be done. These are task doers, not task creators. This is staffing. Staffing works great only if you’ve got the leadership corps ready to mobilise and direct a new group of contributors that are both unfamiliar with your business and your systems.

Consulting: Rather than buying additional time as your primary commodity, you’re looking for thought leadership and expertise. You need a consultant. Someone that has domain specialisation for a particular project you need to complete. You will pay more for a consultant, but you will be getting more. It’s the same thing that I covered above about looking for the unicorn when you hire. Think about your costs as a total overall cost vs. a per hour / day comparison rate to rate. A great consultant is worth three to five staffers in their capability of achieving goals and empowering those around them to a higher level of affect.

I manage a consultancy, so I’m speaking from my everyday experience. We do a little bit of staffing and a lot of consulting. We’re built to be the SAS commandos vs. the Napoleonic land army that you’d find in the Big 4 consultancies. There is a time and a place for both.

Summary

Adding people talent requires a blend of the three options above: add, advance and augment. If you do all of them well, then you’ll have a steady influx of junior talent with the occasional senior unicorn, the ability to create the next generation of data leaders, as well as an elastic bench of trusted consultants when needed.

Talk with local consultancies about their different models to help support you as well as to find the best commercial model. We, of course, are always happy to help.

Just remember, strong leadership is critical to defining your goals and making the daily adjustments to ensure you get there. This the perfect segue into our next common challenge: data strategy.

Want to Learn More?

Find this information helpful? There are more blogs to come with more information on other pain points and the best solutions to ease the pain. We started with data governance and covered people resourcing, but stay tuned to see what the next biggest pain point is or read more in the full white paper.

Know your challenges but don’t know where to start in solving them? Reach out to our team, and we can help you figure out the best solutions for your needs.