3 Rules for scaling your team for greatnesson 24 September 2019 for Companies
While digitalization is improving people’s lives, it is also forcing companies to innovate rapidly. The growth of the internet of things (IoT), for example, has brought about enormous changes to the way that people live, how they shop and how they communicate. Smart sensors within internet-enabled devices now let people do everything from ordering milk via Amazon’s Alexa to turning off their bedroom lights via their smartphone whilst at work. However, while digitalization is improving people’s lives, it is also forcing companies to become hyper-competitive in a way never seen before.
This year will see over a hundred million square feet of retail space shuttered globally yet the number of cashier-less Amazon Go Stores is predicted to rise. Just as Deutsche Bank was announcing plans to slash over 10,000 jobs worldwide, China Construction Bank was busy opening branches in Shanghai managed entirely by robots. The same tech trends that are driving the IoT – Artificial Intelligence (AI) and Machine Learning (ML) – are forcing companies to become leaner and more efficient than ever before.
Therein lies the paradox: the choices for hiring and expanding an IT and Engineering team have never been greater, yet companies are more constrained than ever in terms of who they can hire and the remuneration they can offer. In Belgium, for instance, there are currently over 16,000 vacancies for IT jobs. According to a 2017 BNP Paribas Fortis survey of 100 Belgian companies, 83 percent of firms reported ‘significant challenges’ in finding the right employees.
The central problem facing firms is, with limited budgets, how they can scale their workforces and IT and Engineering teams? How can they find the best, most suitable employees from the available talent pool? In this blog post, we’ll take a look at the recruitment approaches taken by some of the companies that dominate the tech landscape. What rules can we learn from their successes? Here are three rules for scaling your team for greatness.
Rule #1. Focus on efficiency; avoid the team-scaling fallacy
Since the early days of Amazon, Jeff Bezos has followed one simple rule for scaling his workforce: The Two-Pizza Rule. His method for scaling teams was simple: if the team needed more than two pizzas to feed itself during a meeting, it was too large. This one simple concept kept teams small and reduced bureaucracy. Meetings were easier to schedule and projects were simpler to oversee as fewer people were involved. As Amazon is now the world’s largest retailer, the results of the two-pizza approach are self-evident. But why does it work?
Many leaders and managers fall for the team-scaling fallacy; adding more people to a team is always good. If your employees are your best asset, adding more assets should improve performance, right?
In fact, larger team sizes embolden people with confidence that doesn’t always translate to real-world success.
How can you incorporate Bezos’ Two-pizza rule when deciding how to scale an IT team for greatness? You should focus on effectively managing employees so that they work efficiently and you should avoid the team scaling fallacy. This means finding the best roles for workers and not pigeonholing them into positions where they are unproductive. The lessons from Amazon are clear; keep teams small and look for ways to avoid unnecessary hires.
In terms of efficiency, you should also look for ways to spend your recruitment budget as efficiently as possible. So, how can you find the best employees in the most time- and cost-efficient way?
#2. Harness AI and ML to improve your recruitment practices
First of all, AI and ML-based recruitment practices may not be a replacement for face to face interviews. But they do make recruitment processes more effective and more cost-efficient. In order to increase retention, the emphasis should be on finding the best fit between the candidate and organization from both a job and a culture perspective.
According to Forbes, making the wrong hire can cost the average U.S. firm over $200,000. Such is the pressure on recruiters to make the right hires that even top firms including BP, Expedia and Vodaphone are turning to ML-powered solutions. Several startups are already helping firms to identify the top talent using search processes driven by ML algorithms, especially at the top of the funnel. How do they manage this?
Unlike human recruiters, AI and ML-based search procedures are immune from human bias and prejudice. They are better at identifying what candidates can and can’t do, not what a human recruiter believes they are capable of.
Candidates selected by ML-powered selection processes are better matched to positions because human prejudice and bias don’t come into play to such an extent. While these types of search techniques can never be a complete replacement for face to face interviews, they do get results.
Using AI- and ML-powered search processes can make your recruitment process more efficient and more effective. The time that you devote to conducting face to face meetings and interviews will likely be more productive as a result. Better still, the candidates you choose will be better suited to their new roles and will help improve the effectiveness of your team.
#3. Collaborate with coaches, not recruiters
Perhaps you have an established recruitment process such as a young graduate programme. What should you do then?
While AI and ML-based firms certainly have the potential to help improve your programme, we believe that the real answer to scaling a team may lie with human coaches, not computer algorithms.
At Exellys, we match ambitious companies with the finest tech talent. Our goal is the perfect fit: the right talent in the right place. We are specialized in attracting and integrating promising tech talent for large and medium-sized companies and for major tech startups in Belgium. During a two to four-year training and coaching track, we bridge the gap between the academic and business world by creating the ‘ideal incubator’ for young professionals.
As experts in talent acquisition and talent management, we enable our clients to stay focused on their core business and growth.
Ultimately, the key to scaling your team is to find ways to spend your budget more efficiently and think long-term. The main lesson to learn from Amazon’s success is to avoid the team-scaling fallacy and to focus on efficiency – both on worker placement and recruitment practices. From multinationals such as BP and Expedia we can learn that while AI and ML-based recruitment practices may not be a replacement for face to face interviews, they have the potential to make recruitment more effective and more cost-efficient. Ultimately, we can learn that introducing a coaching aspect can be a positive addition to an existing recruitment process.
Overall, nurturing talent through a combination of training and coaching can be one of the best ways of scaling a team for greatness.
If you believe us, get in touch, we’d love to tell you more about our approach. Or read why a Tech Talent Scout at Exellys is so much more than a recruiter.Tags: coaching , scaling , talent attraction , talent development , talent retention