The Mathematical Case for New Hire Training

Multiple studies show a correlation between a robust New Hire programme and increased retention, reduced turnover and enhanced productivity of new hires. Yet, New Hire training remains an unmanaged spend in many organisations with an overwhelmed new hire shuttling between HR, Corporate L&D and business training teams, scrambling to hit the desired performance mark.

Here, we explore three levers that have helped us deliver high-impact new hire training that has:

  • Reduced training time
  • Reduced errors in the first year of the new hire
  • Enabled higher productivity in first year of the new hire

New Hire Productivity

If you are running an averagely effective New Hire Training programme, this is what your new hire’s net contribution graph probably looks like.

New Hire Net Contribution

The X-axis represents the days that the new hire has spent in the company and the Y-axis represents the percentage of the expected net contribution to business.

Assuming that you have a four-week new hire training plan, the contribution by the new hire during this period in training is negative. The new hire is not contributing to the business, whilst the business is investing in salary, space and training. Many of us recognize this deficit in net contribution and account it in the total cost of new hire.

However, what many of us don’t recognise and plan for is the further dip in net contribution of a new hire on day 1 on-the-job. In the first 30 days at work, many new hires make “errors” that add an additional cost of non-performance, dragging the net contribution further down.

It typically takes eight months or approximately 240 days for a newly hired employee to reach the expected productivity [source] and nearly a year to match the productivity of an experienced role holder.

Levers for Optimising New Hire Training

Looking at this mathematical representation, it is easy to identify three key levers for enhancing the effectiveness of your new hire programme.

1.   Reduce the time in training

At NIIT, we have worked with our customers to reduce the new hire training time by 30% on an average. A combination of strategies have helped us achieve this. These include:

  • Staging the curriculum based on the job progress of a new hire.
  • Creating more training hours in a day by reducing the commute time to work for new hires.
  • Reviewing non-proprietary content that the new hire can master even before tsey join the new hire training programme.

For a 4 week new hire training programme, 30% reduction translates to a saving of 1.2 weeks or in other words gives back to the business an additional 1.2 weeks of productive time.

Impact on productivity due to time reduction

2.   Reduce the errors on day 1

We conducted a study for a back office operations of a bank and found that the floor managers were very reluctant to include new hires in their teams. One of the key reasons was that the errors made by new hires were substantially high which negatively affected the overall operational metrics of the team.

Critical Mistakes Analysis© (CMA) is our proprietary methodology, based on over a decade of research at Northwestern University. One of the key insights from this research was that the only difference between an expert and a novice is the experience. Typically, an expert has been exposed to many more situations and is therefore able to tap into their prior experience of the situation to deal it with more effectively.

Using CMA, enables us to identify the most frequently occurring situations a new hire will face in their first year. By coding these situations into the training and enabling the new hire to interact with them, we can substantially reduce the learning curve and reduce the errors on the job in the first year.

If CMA helps us reduce the day 1 errors by 40%, we can accelerate the time to minimal errors by 3 months.

Reduction in errors helps enhance the net contribution of a new hire.

3.    Reduce the time to full productivity

Bringing learning closer to an opportunity for application on-the-job helps enhance the effectiveness of learning. Further, since the key difference between a novice and an expert is the experience, coding experience in learning scenarios helps accelerate learning. Using this design methodology, we enable new hires to experience most frequently occurring scenarios in their roles. The scenarios, presented realistically, enable them to apply the learning in real life-like situations. Thus, when the situation actually occurs on the job, the new hire is already ‘experienced’ to manage it.

By implementing these levers, we can shift the net hire contribution as displayed in the graph below.

The orange line represents the net contribution of a new hire who has gone through an average new hire programme and the blue line represents the net contribution of a new hire who has gone through an enhanced new hire programme.

New Hire Net Contribution

The Mathematical Case

To translate this impact into dollar value, let us assume a new hire whose salary cost is $5,000 per month and the total loaded cost, including both direct and indirect costs salary, benefits, admin, shared service, office infrastructure, utilities etc.) is $8,000 per month. The expected productivity contribution from this new hire is $15,000 per month.

The four-week training cost for this new hire is $2,000 and the cost of errors in month 1 is $5,000.

The table below captures the net contribution made in:

The Mathematical Case

a)      Scenario 1 with average time to productivity

b)     Scenario 2 with the optimisation levers described above, based on NIIT best practices

This is 129% higher contribution!

Isn’t it worth reviewing your new hire training to find opportunities to optimise?

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