It is an exciting time for workforce analytics, and many individuals and organisations are showcasing the benefits across a whole range of initiatives dealing with performance, diversity, engagement and productivity resulting in workforce analytics growing up as "disciplined function within the business" - Josh Bersin.
The methods used are just as diverse and include practical ways to aggregate and visualise, machine learning, prescriptive analytics, strategy frameworks and techniques to automate to increase team productivity.
While there has been considerable progress, organisations that I have worked with, while they can generate useful insights, struggle with meeting the new demands of the business ensuring an enhanced level of quality is achieved, while increasing output.
This article focuses on one way to increase the level of frequency by combining existing business KPI's with metrics that focus on the employee's lifecycle within the organisation. This combination will not only make process and policy decisions more comfortable; it will enable you to tap into the attitudes and beliefs relevant to career stage.
Create a diagnostic capability
The creation of a diagnostic capability, akin to a doctor asking a range of questions, will enable you to narrow in on problem areas. One mechanism to allow this is tailoring a variety of workforce metrics and models to critical parts of an employees lifecycle.
An employment lifecycle should cover everything from hiring to separation and could be broken into the following; Acquisition and Onboarding > Movement > Engagement > Maintain > Separation.
A monthly reporting cycle, where the business partner or analyst, views each aspect of the employment lifecycle to understand trend and thresholds will enable the consumer to question relevance and alignment to strategy quickly. The below outlines areas of opportunity, try to start with one or two areas and get feedback from the business as to suitability.
Barriers to this view include data complexity as processes tend to be tied to a variety of different processes, expertise in automation allowing for a regular review 'temperature check' and tools to quickly identify insights. These barriers can be resolved quickly with the right expertise, feel free to reach out if you need help.
Acquisition and Onboarding
From application through to hire, understand conversion rates by different dimensions, i.e. gender, role, internal/external. Do these align with current strategies? Areas of analysis include;
Impact of time to start on quality.
Recruitment costs both direct and indirect.
New starter retention rates with replacement cost.
Cohort retention, i.e. graduates, critical roles, indigenous employees.
Competitor in/out ratio
Requisition failure rate by role - understand emerging short-fall roles.
Employee Movement Analysis
Creating meaningful work is a challenge. This can be enhanced by understanding how people move throughout the organisation and level of satisfaction with the career. Initiatives in this area can help to strengthen workforce planning strategies and promote higher employee engagement. Areas of analysis include;
Create a 'labour market map' by combining key metrics such as external in's, internal in's, promotions, internal out's, external out's and segmenting by business unit and role over a 12 month period.
Internal movement success laterally or promotion will help to inform and make improvements to mobility strategies.
Explore diversity cohort mobility as a comparison to group norms. This may help make improvements to diversity strategies.
Dive deeper into career satisfaction collected through a monthly sentiment survey. Averages can be misleading, explore upper and lower quartiles by leadership levels and business unit.
Keeping track of engagement can be tricky as it usually requires high input from employees, therefore a once a year process. The reporting method is improving in frequency and accuracy with organisations moving to monthly pulse surveys and passive ways to gauge engagement.
Through greater reporting frequency, set up correctly, you can quickly act on the trends by viewing dimensions such as role and demographics allowing you to make tweaks to workforce strategies with the aim of improving engagement. These methods include;
Pulse survey, random sampling: All surveys should be tracked to ensure pockets of employees are not overburdened. Focus on sampling around 10% of the population on a sentiment or pulse survey with key engagement questions as well as other questions relevant to the time. Compare spot-month engagement score with a rolling average ~3 months to create insight across varied dimensions.
Passive scoring: Start modelling the engagement score with variables that you think might be useful predictors of engagement. These could include workload through timesheet, business performance, absenteeism, leadership effectiveness, retention rates, team performance, etc. Once variables have been selected, model these to understand fit and test the predicted scores to ensure this is useful.
Improving diversity strategies may benefit from having access to centralised data that give an overview of a range of cohort groups in comparison to the group norm. These may include female leadership, female employees, indigenous employees, equity groups, veteran and employees from another nationality. Areas of analysis include;
Pay parity: This is a top concern for organisations as it does affect employer brand. There is also an area that is often in the spotlight, i.e. recent class action on the pay gap.
Participation parity: Parity at this level may be tricky due to the industry the organisation operates within, types of roles required etc. but it pays to ensure parity at different groups such as women in leadership, women in boards, equity groups and parity in the community is met.
Promotion rate parity: How do female promotion rates compare to the female participation rate and how does it vary by role and tenure. Where employees have the same tenure and performance outlook, are there any material differences as this could indicate bias. This could be expanded to include a range of mobility metrics.
Some organisations conduct regular exit surveys to understand why people leave the organisation, fewer understand review sites such as Glassdoor. This is an untapped area of analysis, and it is starting to be more than collecting information about someone who has tendered resignation and moving into predictors that look at employees thinking about leaving. Areas of analysis include;
Exit surveys: a simple survey to understand where improvements to culture, leadership, ways of working could be improved. To make this more useful; try linking this data with profile information, performance, succession plans and business unit. Start to piece together why employees have given a negative or positive result, is there a trend? Use this to inform people strategies.
The potential for leaving: Machine learning was big for 2017, and many companies are starting to place a range of variables into machine learning models to understand the likelihood of an employee leaving the organisation. Success with internal company data can be challenging if the variety of relevant data points have not been established but there are a few techniques that can result in high accuracy by using only one or two variables. This type of intelligence can be a great way to reduce the number of regretted hires as it is more forward-looking and could result in the creation of broader interventions to improve productivity and engagement.