Chaos theory focuses on the premise that even in what appears random events there are patterns. It’s the idea that small changes can have ripples that may cause significant impact. It is sometimes referred to as the butterfly effect or nonlinear dynamics — and you could argue techies check for it via regression testing.
Linking chaos theory to managing workforce change may seem like a stretch, but I would suggest if you are focused on predicting the future as part of your workforce planning, you might end up getting a practical lesson in it.
This was the problem for any future of work agenda before the COVID-19 pandemic, as the guide rails were so broad and timelines are, if you really think about it, infinite.
At Aon, we focus on the practicalities of execution. For us ‘Future of Work’ is really ‘Workforce Optimization’ and that means focusing on the following 4 pillars:
- Evaluate and Optimize People Spend - understand the ROI on your people spend and quantify outcomes
- Manage People Risk - analyze proximity, innovation, failure to change, reputation, pivotal talent and diversity & inclusion to name a few; these risks are hard to avoid altogether and instead need to be mitigated
- Empower Agility and Resilience – if predicting the future is to attempt to understand chaos theory then the answer is in building the capability to adapt and evolve long term flexibility regardless of the catalyst
- Build Stakeholder Value – I would suggest if you focus on 1 through 3 above and balance employees, shareholders, regulators and clients this should be the real outcome of a “future of work” agenda.
The Problem of Accelerating Change
The COVID-19 pandemic has provided some 20:20 hindsight on why workforce optimization is essential for all organizations. It has accelerated the need for change. Even more importantly, it has given employers a sense of the opportunity available through a future of work agenda and the ability to deliver on all four pillars above.
However, making changes means making decisions that are often aligned to an individual pillar and the questions asked are somewhat binary, such as:
“How do we cut costs?” or “How do we improve our diversity?”
No one would argue these questions are not relevant in the current environment. However, thinking in isolation like this is where ‘chaos’ ensues because the ripples of cutting cost has potential to impact diversity.
By focusing on one issue in a silo, firms can end up creating new problems potentially long after solving the immediate issue.
The Solution: Focusing on the “AND”
To optimize the workforce, we need to think beyond the immediate impact of decisions and outside of data silos. If we do, we can start to ask much more onerous questions like: “How do we cut costs, AND ensure we don’t cut into muscle AND compound a diversity issue AND develop future skills?”
The AND is required to recognize there are correlations in cause and effect.
Solving the future of work is about making informed decisions that allow you to understand the immediate action to be taken but also the ability to appreciate the follow-on impact (good and bad) of that decision.
Building the Central Intelligence of Workforce Analytics
Most decision making these days is informed by some form of data and analytics. Normally it’s limited to a data silo. Expense management will look at drivers of cost; talent will look at capability; workforce planning looks at pay equity, and so forth.
But the future of work is about digitalization, breaking down silos, collaboration and democratization. We already undertake a huge amount of analytics but to solve the AND questions we need to start joining data up.
In a recent thought piece, my colleagues outlined how HR should rethink workforce metrics. Gaining an understanding on these is powerful. But if you can gain transparency on all of them together and extend the analysis to encompass information to identify risk (and its variants), cognitive diversity, skills and capabilities, you gain the ability to understand the levers they can pull and the impact it might have elsewhere.
This process is also inclusive. It can build employees. Employees help you capture information on how the workforce is changing and they do so because they get insights returned to them, not just on their personality profile, but also suggested roles they might wish to consider and potential training intervention, which can drive mobility and development. More importantly, in combination you start to see the return on investment and potential savings through build or mobility strategies. Future of work becomes much more meaningful than hiring data scientists or developers. You begin to see how this changes workforce demographics over time.
By building the central intelligence of workforce data, layering in market intelligence and engaging staff in the process, firms gain transparency on the complexity and interconnected nature of the workforce. This allows them to balance clients, shareholders, regulators and employees and build a diverse workplace designed to drive productivity and tailored working environments.
After all that’s what the future of work is about: building a workplace that enables humans to be the best they can to help drive better outcomes.
So, while predicting chaos theory might seem like an insurmountable challenge, when it comes to appreciating the patterns and ripples caused through workforce change decisions, we can at least be better informed through data analytics.
The future of work needs the right data and analytics to provide better transparency and it looks a little something like this...
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