Over the last two decades, I have spent many years working in the commercial sector. During that time, I have worked with a few services organisations on workforce analytics.
In the past, typical scenarios or use cases for workforce analytics included:
- The classic problem of travelling sales teams, and how to minimise their time on the road (Travelling_salesman_problem). This is a classic optimisation problem that has more recently morphed into minimising supermarkets’ commercial fleets delivering goods from regional distribution hubs to local supermarkets. It is also useful to ensure that home engineers from utility providers and similar maximise the time they spend fixing boilers and servicing central heating rather than travelling to jobs. This also has environmental benefits.
- Optimising contact centre staffing to match high retention-risk customers with the most experienced staff to minimise the risk of cancellation/churn.
However, more recently, the focus in workforce analytics has shifted to a more holistic approach to talent and workforce management and optimisation. In particular, organisations increasingly use it to improve employees’ mental and physical health.
Managing a workforce of thousands
Why is this so important? Let’s take the UK’s public sector as an example. According to the recent Institute for Government’s Whitehall Monitor, there were 419,120 full-time equivalent civil servants in September 2019, which means that in reality there were far more individuals. This is a massive workforce. And budget-constrained government agencies pay a huge cost for its recruitment, training, retention and remuneration. There are obvious ways to use analytics within these organisations to retain staff for longer, recruit the right people, and identify and fill any skills gaps.
Getting these issues right matters for organisations because of the costs. However, there are other, hidden costs to getting it wrong, in time off sick with stress or other mental health problems. These are just costs to organisations but devastating to individuals.
What’s more, the figures for mental health problems are rising around the world. According to Happiful, the UK had a reported 15 million sick days in 2016 related to mental health issues such as stress, depression and anxiety.
There are some initiatives going on that should help. For example, last year, I trained as a Mental Health First Aider to help people in my organisation to identify and manage mental health problems before they become a big issue.
Supporting individuals, solving problems
However, I think we should also use analytics to look at staff welfare issues. For example, we could use analytics to examine working patterns and identify triggers for stress-related illnesses. Or the most effective return-to-work practices for employees returning to their jobs after a longer period of sickness absence. These applications would help organisations to optimise resources. But crucially, they also ensure that organisations can better support employees with mental health problems.
The potential applications for analytics to improve workforce mental health in the public sector are vast, and might include:
A recent study identified rising physiological problems among teachers and suggested that the school workforce is being pushed to the breaking point. In total, 75% of teachers class themselves as "stressed." And one in three education professionals has experienced a mental health issue in the last academic year. Analytics could help to identify emerging trends and problems and determine where best to focus limited support services.
A bulletin from the MOD noted that 2.7% of UK Armed Forces personnel were reported to have a mental health disorder. And research has found that anxiety and depression are twice as common in the armed forces than elsewhere. Again, we could use analytics to look at patterns and trends, as well as what works by way of support.
Over the last decade or more, the news has been full of reports of stress within the nursing profession. The UK’s Royal College of Nursing says that workplace stress is often cited in compensation claims and frequently associated with inadequate staffing levels. Retention of nursing staff is a huge issue amid claims that the NHS is recruiting too many staff from developing countries that can ill-afford to train and then lose qualified nurses. Modelling demand and trends could help to identify problem areas and improve workforce planning for the future.
More interestingly, analytics can also surface hidden issues by looking at new sources, such as social media. It might, for example, be possible to identify hot spots of stress within particular units, specialties or hospitals. These could point to more systemic problems, such as bullying or an unhealthy culture, which need very different solutions from "a shortage of nurses."
An obvious step
I am really fortunate to work for SAS, an organisation that takes its employees’ physical and mental well-being seriously. However, more and more organisations are realising that they need to do the same. The use of data and analytics to spot trends and determine the effectiveness of strategies seems an obvious next step. Take a look here for further information.