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PAYmodelling - Managing Reward Data

Our customers have always used us to design their reward schemes. They would then implement these themselves. This remains an important area, but our customers are now increasingly asking us for help in managing their reward data.

Our PAYmodelling service helps you to manage your reward data. For example we can:

develop your salary ranges;
calculate the pay review cost;
model pay for performance awards;
review your equal pay practice.

This can be more cost-effective and faster, and means that you can focus on the areas that are most important to you.

Pay modelling starts with understanding the market. Our salary surveys provide you with clarity about market pay rates. But the power of a salary survey is being able to turn it into policies that you can apply to your people. We adopt a simple and well-proven process that makes it easy for you to give managers the tools they need to make the right pay decisions.

Step 1 – Organising your data

If your feel that your HR data is not as good as it should be then you are not alone! By far the majority of our customers need help to rationalise their job titles and to apply job evaluation principles to levelling their jobs.

Our PAYmodelling database forces a disciplined approach. It groups jobs into families and standard roles, and organises them into levels. If you have a structured approach in place, we will use it. If not, we can help:

We can use the job families and levels that underpin our salary surveys;
Perhaps you complete a salary survey which has grades and job descriptions. We can use your job matching to guide us.

Step 2 – Organising the market data

We are able to bring together data from our salary surveys and salary surveys published by other providers. This is because we understand how all the major salary surveys work. We are also able to use data from other sources. This is organised into exactly the same structure as your internal data.

Step 3 – Creating the market guidelines

We can now bring together your internal data and the market data. It is nearly always the case that each market source will show different results. This is where we use our reward expertise to interpret the results and create a market guideline for each role. A really useful “traffic light” report highlights roles that are under or over paid compared to the market.

Step 4 – Developing the salary ranges

Published salary scales usually show a smooth progression in pay between job levels. They also tend to adopt some rules about how wide (minimum to maximum) the scales should be.

We take the market guidelines created in Step 3 above and turn them into salary ranges that you can publish and use to manage pay. When doing this we apply a novel approach which our customers have found very useful. This is to divide the range into three sub-ranges – you can see how this works in this example. The idea is that:

The first range represents the zone where we would expect to find either new recruits or people new to role;
The second zone contains the market position and shows the pay range we would expect to apply to most people in the organisation;
The third zone is above market and shows the pay range for people who deliver high levels of contribution.

Step 5 - Impact and distribution analysis

The impact analysis shows the people who are below the minimum of the pay scale or above the maximum of the pay scale. This is useful in fine tuning the scales.

The distribution analysis shows the distribution of people through the scale. This provides data that they can use to manage pay.

Step 6 – Pay for performance

We now bring in the performance rating of each employee and use the salary scales to determine how well they are paid. From this we create a report for line managers to help them manage the pay review. We can also calculate a pay-for-performance matrix that further guides managers in making their pay decisions.