Using AI to reduce workforce attrition

For a corporate client in the AI tech sector

For any business, employee turnover is natural and to be expected within the workforce. People join, people leave and people are replaced. 

But attrition leaves a hole and it’s a hole that is not always easy to fill. Particularly in specialist sectors such as technology, where specific skillsets and knowledge are at a premium. The pressure is continual when it comes to your skill-base; you never have enough because by the time the market has produced them, it has already moved on.

Workforce attrition can be damaging not only in terms of company performance and outcomes but can also diminish morale, putting more pressure on existing staff who are asked to take up the slack, performing tasks they are not equipped to carry out, leaving them frustrated, overworked and looking for the exit sign. Which of course, leads to further attrition and a lack of business control.

Key causes of high employee turnover include lack of growth and career progression; excessive workload and lack of feedback and recognition.

Research from XpertHR found that employee resignations reached a five-year high at 15.5 per cent, in 2017.

The financial cost of replacing a key employee can be steep, taking into account recruitment, training and on-boarding and other hidden costs, the average employee costs £11,000 to replace, according to small business accountancy specialist, Accounts and Legal.

The key is to extend Employee Lifetime Value, which starts in the minus when employees first join because they are not yet contributing to the company. Using employee data in the right way is the key to reducing attrition at the end of the cycle so that employees continue to add value and extend their tenure, contributing for longer.

Applying the same rigour to workforce science as say, product development and brand strategy can be hugely beneficial to companies in terms of productivity, team dynamics, morale, continuity and company perception. Businesses recognised as great places to work inevitably attract the best talent. Furthermore, they retain it. 

Management concerns

And yet, despite the obvious benefits of good HR policy and a healthy internal employee culture, the danger of decline should it be otherwise is not paramount in the minds of business leaders.

PWC’s latest CEO survey says the threats that trouble CEOs are increasingly existential and external.

Gartner’s 2018 CEO survey cited laws and regulations, competition and financing as the top three external challenges. Internally, however, employees, talent and skills took top priority. Lack of appropriate talent and capability in the workforce has been cited as a top inhibitor to digital business progress.

• According to the survey some 42 per cent of CEOs with digital initiatives are looking to make significant or deep culture changes by 2020.  

• The top two tech-related skills needs mentioned by CEOs were data and analytics and digital

• Only 28 per cent of CEOs in the survey identified Workforce as a top five business priority over the next two years.

The intelligent approach

Positive approaches to increasing employee lifetime value always start with hiring the right people at competitive rates but people want much more than just a good financial package, they want opportunities for growth and a feeling that their best efforts will be effective and rewarding for them and the company.

The opaque nature of people management means that workforce science, unlike real science, is often far from exact, which can produce the wrong results, leading to the onset of attrition. So maybe a data-driven approach is the best way to resolve the issue?

One tech consultancy company believes so and has created a bespoke AI product, which interrogates the data created by businesses and the people who work in them and helps companies to maximise the value they get from employees across the life-cycle of employment.

It addresses the issue of attrition by optimising the chances that:

• the right people are recruited for the right role 
• existing employees are deployed on the right work 
• they are given appropriate and fulfilling work and are therefore happy and productive 
• and increases the likelihood that they will stay and grow with the company.

By putting  together employee data from across the organisation it ensures that effective decisions are taken based on the evidenced reality of employee performance (rather than e.g. interview ability), qualifications and role suitability. 

It sifts through the data a company already owns or has access to (CVs, project documents etc.) to understand the talent pool, for example qualifications, achievements and project work, to rapidly uncover skills:

• Known and quantifiable skills, e.g. qualifications
• Unknown skills, e.g. soft expertise, experiences, potential career trajectories

Using artificial intelligence and machine learning on existing data, it builds a map of an organisation’s competencies and capability, automatically, in real-time and in collaboration with staff. This typically includes company-specific topics, e.g. project names and acronyms, as well as more generic skills and capabilities.

Once it is part of the network, the programme will automatically update an organisation’s ‘corporate memory’ with new data and new knowledge about the staff and the resources available.

In a world where change is constant and the ability to respond is a prized asset, labour needs to be flexible. Using this AI product you can understand the talent you have today and your people needs tomorrow, to hire right, retain the best and eradicate needless workforce attrition.