What is the Link between Sales Forecasting and Kpis? How to Find the connection

Pros And Cons Of Obama Health Care Reform - What is the Link between Sales Forecasting and Kpis? How to Find the connection

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I propose the link is the relationship between working capital management and the reliability of the sales forecast.

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Pros And Cons Of Obama Health Care Reform

Let me construe my logic.

The top levels of your performance indicators are your sales Kpis. They are the drivers of the income line in your accounts. More importantly the DuPont model recipe shows that an growth in sales without an growth in your funds employed has a multiplier ensue on your company return. That simple, irrefutable fact is the guess that good working capital management is so vital.

Revenues are the prime source of your working capital. If they shrink below your cost of goods and your expenses, you are provocative capital, and your solvency is at risk. One of the ideas of working capital management is that you should keep your stock levels and fixed costs in a reasonably carport relationship to your sales. Fail to do this and liabilities will inevitably rise as your cash flow turns negative.

Because costs are incurred before sales can be made, to keep the two in equilibrium you have to predict sales and plan your present commitments to match the prediction. If you under- or over-estimate sales, you will have trouble whether in supplying your customers, or in filling up the store with slow provocative goods.

It is even worse in a aid company because you cannot store time. Your habitancy resources are a fixed cost in the short term. Economists call them "sticky" because it is hard to juggle them at short observation like a yield schedule.
The safe bet ensue of whether condition is a cash flow problem. The only demand is "How long does it take for the wave to roll up from behind and swamp the boat?" The uncomplicated fact is that inaccurate sales forecasts are a huge source of inefficiency in every business. All your efforts to fine-tune your company by performance determination and management are futile if your sales forecasts are wildly inaccurate.

Kpis and important Indicators.

Some of the most beneficial Kpis reside in the sales and marketing arena. These are the ones that act as important indicators or predictors of a turn in demand. If your forecasts are based on your real Kpi buildings then they will give you develop warning of turn and enable you to take early action to respond, whether in your sales tactics, or in reallocating resources within the business. whether way, early response is a good competitive move.

An example:
If your company has a long sales cycle, a turn in the value of the prospects in the early stages of the sales cycle will signal a turn in the value of hereafter cash flow well in advance. If you pick up the signals before competitors, you can take the lead. A probability based forecasting model works particularly well as a important indicator Kpi.

The good news.
If you use the right techniques and the right forecasting models, you can dramatically enhance the accuracy of your sales forecasts. If you work on this you will enhance company efficiency and overcome the mismatch of resources that is so destructive of everything you have worked for.

Why are so many businesses dependent on a deficient forecasting model?
I believe there are many reasons for belief on inadequate forecasting techniques. Do any of these fit your business?

Masses of data but dinky high ability information. It is hard to sort data if you do not know what is relevant. This is the guess buyer and product segments are so important Sales data is too often $ numbers only. Quantity and action numbers are hard to get from the accounting system. This make it difficult to reply the all-important "Who buys what?" question. shop segmentation is dinky or out of date. This is the best guess to use your Kpi model to find profitable shop segments. Staff are not good at forecasting. There is no systematic advent or discipline. They rely on over-optimistic guesswork. dinky knowledge of statistical forecasting techniques. This is a question with our education system. There are few courses on forecasting offered in company schools. We don't believe it is possible. If it is not possible, why waste time trying? It's too hard, too time consuming; we are too busy. Nobody in our company can do it so why should we try?

When your sales forecast certainly has to be right. An example from my sales apprenticeship: My first sales job was selling polyethylene to the plastics manufactures while the fastest sustained growth duration in the second half of the 20th century. The manufactures was growing world-wide at a rate between 10 and 20% per annum and it continued for 20 years.

I worked for a major global manufacturer, that had built a new plant capable of supplying nearby 70% of national demand. A polyethylene plant is dependent on contracted supplies of ethylene gas from a refinery, and these contracts are set on an yearly basis, well ahead of the start of the year. This company was totally dependent on the accuracy of the monthly sales forecast set 18 months ahead.Global furnish conditions fluctuated between gross oversupply and global shortages, and yearly demand growth could be anywhere between 10% and 20% from year to year.

Let us witness the consequences of a bad sales forecast in this situation:

If we underestimated demand, our buyer would run short of stock and be unable to furnish their demand for product. They could not secure overseas supplies in the quantities needed, at less than 4-6 month's notice. habitancy could lose their jobs and businesses fail due to failure to furnish raw material. Unhappy customers would depend on imports and the plant would lose vital shop share. If we overestimated demand the plant would have to pay the refinery to burn ethylene gas, or turn it into surplus product.

How did we get the forecast right?
For my buyer group, 70% of tonnage went to just five major customers. A major part of my job was to negotiate an yearly covenant for furnish that assured the buyer of furnish and required a close working relationship on forecast consumption month by month.

I had to put in order an 18-month forecast by buyer and by product grade and update it monthly. This was my lowest up forecast. I also had to collate the total with foreseen, growth rates, both globally and in Australia, and adjust the forecast for major new projects arrival online (The top down forecast), and collate and reconcile the two forecasts.
Did we get it right? 90% of the time we were within 5% on a quarterly basis. It was good enough. I felt very motivated because I did not want the job of telling any buyer that they could not run their installation because I got the forecast wrong.

My next job was Sales Director of an auto component manufacturing business, with similar forecasting problems. Over 7 years we had a proud record; we never stopped a customer's yield line. The disciplines of my apprenticeship had served me well.

Sales Forecasting issues and solutions.

Discontinuities in trends. These are sudden and unpredictable changes in demand, like earthquakes. Even when we know they are going to happen, we don't know when. All you can do is to look out for signs of overheating or cooling and try to be more conservative when you doubt the boom time hype. Many discontinuities are predictable, with causes such as major changes in legislation. A good current example is the Obama condition care bill currently in the Us Congress. Things will change, the big demand is "How?" Discontinuities are no excuse for failure to forecast.

Forecasts are not accurate. All forecasts are wrong, the only demand is "By how much?" The solution: portion your forecast error and make adjustments to your settings, just like sighting in a rifle.

Project (or contracting) businesses are notoriously difficult to forecast, whether they are in building or expert services. The solution: Use a probability based forecasting model. This uses three ideas.

Keep track of every anticipation in your sales pipeline from the first time an chance is identified. The probability of turning a anticipation into a banked check increases as each milestone in the sale process is achieved. The foreseen, Value of the anticipation is the value of the sale x the probability attached to the last completed milestone.

This type of model has proved remarkably reliable for me and my clients for many years.

Products and services based businesses find it difficult to pick out a trend they can rely on. The solution: All trends in company are the sum of three basal trends, namely...

The long-term trend. The company cycle. Seasonal demand patterns.

If you have good data for 5 years or more, and a statistical model, you can fast secure the long-term trend and a seasonal index for your shop or for private segments. The statistical ideas and techniques are well established, and you can get the same results just following the instructions with a good Excel Model.

Top down versus lowest up forecasts. Too many businesses rely on the bosses forecast to set sales targets, then wonder why targets are not achieved by a dispirited sales force. The solution: Top-down rarely produces the right ensue on its own; bottom-up alone is no better. Incorporate the two techniques and focus on reconciling the incompatibility between the two and you are likely to get a reliable result. Sales habitancy can yield a good honest forecast if they are shown how and given the right tools (models) to do it.

Some suggestions for action.
Improving your sales forecasting process and accuracy will all the time enhance your return on funds employed. Forecast accuracy is all the time a key performance indicator, because it pulls every lever in the business..
To make it happen for you, I propose three or four steps:

Review your shop segmentation using a Kpi strategy model, so you are trying to forecast the right parts of the business. Use a scheme Forecasting Model to administrate sales effort. Treat every anticipation as a scheme in its own right for best results. establish your own Sales Kpi model to ensure that you have identified your real Kpis. Use a Trend prognosis model to dissect trends for private segments (if that fits your company better.

I propose you avoid fancy forecasting programs until you understand the ideas behind them. The three models I have suggested will solve 70%+ of sales forecasting problems with minimal investment. The big programs are for big clubs with involved structures, so they have to deal with complexity. They also get it wrong, despite employing high-priced analysts. Remember that forecasting is informed judgment so no one can take the judgment out of the equation. Use models to test your judgment and they will work for you. Use models to take off the need to make a decision and you risk failure. "Keep it as uncomplicated as you can", is still sound guidance for most of us.

I am certainly safe bet that if you use the ideas in this narrative and ensue them straight through you will be able to sleep more soundly at night, secure in the knowledge that you have taken the guesswork out of your forecast.

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