How fair is your employee scheduling system anyway?

The complaints used to pour in every time new schedules were released. Accusations of favoritism and preferential treatment were probably the most common, but they all boiled down to this: How fair is your employee scheduling system anyway?

Things got so bad that planners were beginning to dread their work. Creating schedules was stressful enough without having to deal with dissatisfied employees who were convinced they’d been given the short end of the stick.

But were they?

A big part of the problem was that no one could say for sure.

Some employees used to email their preferences for particular shifts. Others dropped by at a planner’s desk with a special request or gave a planner a quick call. The process – if it could be called that – was the perfect breeding ground for confusion, unhappiness and suspicion.

It was clear that fulfilling a high percentage of employee preferences wasn’t going to be enough. Any new planning system would have to ensure that employee preferences were allocated fairly.

Part of the solution lay in implementing an employee portal where employees could enter preferences, indicate their relative importance, and monitor the results. This was also a great help to planners, who no longer had to keep track of who wanted what – and how badly.

The next step was to introduce KPIs that tracked both the overall acceptance of employee preferences, and how fairly acceptance rates were distributed. While an average acceptance rate of 50% might look good it would, in fact, be a recipe for disaster if 50% of employees had all their requests fulfilled and the other 50% had none.

The complaints soon stopped when employees were able to see for themselves that everyone was being treated fairly. The planners were relieved; morale rose; and significant sums of money were saved with a system that enabled all relevant KPIs – from productivity to employee satisfaction and fairness – to be monitored and optimized.

A hidden cause of unnecessary overtime

Didn’t see that one coming? The key to successful demand planning

By: Wetsun

The business world is more volatile than ever and staying ahead of the competition is becoming more and more difficult. How can your company survive and thrive in this difficult and dynamic marketplace?

The key to staying ahead in the game is to start taking demand planning seriously. Forecasting should be a daily process of gathering information from different sources, based upon multiple hierarchical dimensions, aggregating to higher levels, dis-aggregating to lower levels, and incorporating rules that make the forecasting process manageable. Finally, you must corroborate your forecast with actual orders by using KPIs. Let me explain these points:

1. Use different sources of information

The most obvious source of a forecast is to look at historical sales orders and run a statistical analysis on this. But there are many more sources. For most branches in a company, forecasting information is made available by commercial market analysis agencies and data from the sales organization. Don’t forget that your end customer may also be willing to share their forecast for your products. Analyzing differences between various sources can identify areas of interest that you can examine further.

2. Use multiple hierarchical dimensions

In order to detect trends, it is useful to zoom out and – instead of focusing on the “finished products” level – generate a forecast based on multiple, hierarchical levels. Most manufacturing organizations use hierarchies for both their sales organization (for example, region-country-customer) and product hierarchies (for example, product type – product group – product).

3.  Aggregate/ dis-aggregate

Good forecasting tools should allow planners to aggregate a forecasts to a higher level on product, sales or time dimension. Dis-aggregating to lower levels is required when the forecasting has been done on a higher level. For example, if you receive data on the product type level, and you would like to forecast what this means for lower levels, disaggregation on dimensions is needed.

4. Use rules to manage forecasting

Usually the amount of data involved in forecasting is huge. Not having rules or macros that support the forecasting process can make that process very time consuming. A good forecasting tool should support rules such as this: For product A, use source of information 1 for forecasting the first 3 months and after that use source 2.

5. Corroborate your forecast with actual sales

The current order book can be used to verify the short term forecast. Although there are no guarantees that this forecast will hold true in the long term, it provides a good indication if your forecast is on the right track. Unexpected deviations may point to errors in the forecast. Forecasting KPIs are essential to measure the forecasting process.

What forecasting KPIs do you use to measure the quality of your forecast? Is your company taking demand planning seriously?