Forecasting RM prices has a predictable outcome

RM prices are the most critical driver of the P&L in the short to medium term. Consequently, forecasting RM prices is seen by many companies as one of most important assumptions driving P&L planning and budgeting.

Unfortunately it is also a waste of time. 

Take any RM price forecast by a procurement person and it shows 3 months of stable prices, follow by price increases. Any chart that compares forecast prices to actual prices over time will show a pattern like this:

procureanalytiq procurement analytics

This is because you are combining the unknowable with the management of expectations. It results in a realistic worst-case scenario. And it cannot practically be challenged. 


Eliminating uncertainty

Of course, eliminating even a little uncertainty would be tremendously valuable. And it makes sense to see forecasting as the cure for this uncertainty but, like alchemy, the only potential rewards of forecasting are fools gold.

Existing knowledge and expectations are already priced into basic commodity prices and FX, and movements up or down are equally likely.

Therefore trying to predict commodities prices the same maths as tossing a coin. If you can toss the coin 100,000 times, I can give you a guaranteed 100% accurate forecast. But that knowledge does not help you when you only toss it once. You will average 50% correct and 50% wrong.

Still, here are some ways on how people take a view on commodity RM prices, and why it does not work. 

Take a macro-view

One option is form a view on macro-economic events. Will OPEC increase supplies, will a major war break out, will the federal reserve do more QE.. etc. That is OK for when you stand by the coffee machine. But, unless you have inside information, this is no better than gambling. And if you are not willing to bet your own wealth on that outcome, then you cannot do it with your company’s money either.

Anticipate long-term trend will continue

Your other option for forecasting is to look at long term trends, and to anticipate that those will continue. And for sure they might. There is no shortage of talking heads making money by forecast straight lines. (Admittedly it is probably a better business-model than this blog.) But it is 50% likely that a different “expert” will be forecasting a different straight line in just a couple of months.

Use technology and AI

And sure, there are many big technology providers out there claiming that AI will be better at predicting commodity prices. But my view is that bigger computer and smarter AI programs will not help you improve any forecast into the future much. But they will be happy to take your money trying….

Here is a small example of prediction of Oil prices. You cannot get more basic and fundamental than oil as a driver of the economy and of the future. If we cannot forecast oil, we might as well go home.

procureanalytiq procurement analytics

So I would summarize the conclusions as follows:
– We forecast no change in prices for the next 2 years
– We are 95% confident that it will not go below $20/barrel and not above $100 per barrel.

That is the outcome of applying technology to commodity. They will run 100,000 scenarios, and come to the mathematical conclusion that today’s price is correct.

Until it isn’t, of course. 

Of course, that is not to say that there is no use of technology or AI. And neither am I  suggesting that you stop planning the future Profit & Loss. My point is that your effort is better spent on doing 2 things:

  1. Use what you already know, rather than forecasting the unknowable.
  2. Build a business that is resilient to RM price volatility

Ways to plan your future P&L without doing any RM forecast

In some ways, making assumptions about future RM prices seems the critical assumption about your future P&L. Here is some guidance on how to plan your P&L


1) Use the information on RM prices that you already know

Depending on the supply and production lead times, it is likely that your P&L is running about 4-9 months behind the prices that the procurement team are agreeing with their suppliers.

A price that is agreed for a full quarter in late-December, will still be on the Purchase Order to a Chinese supplier in mid-March, which will get produced at end-March, which will be leaving a dock in China in early April, which will be clearing customs at destination at end May, which will be used in your production in June/July and sold to customers in August/September depending on demand and inventory.

So the price agreed in December will hit your P&L as late as September. So in part you already know the RM prices that will hit your P&L 9 months from now.

Of course not all RM have a quarterly prices and 2 month supply lead-times, and inventory levels will be lower when lead time is lower. But many do. Are you clear on exactly the time lag between price negotiations and the time those prices hit the P&L? I guarantee it will be at least 4 months on average.

FX can also disrupt this analysis, which is why it may be worthwhile to hedge genuine FX exposures in the short term.

The starting point in your P&L analysis is therefore to have complete clarity on what you should already know. And that is work for the finance/controlling team, not for the procurement team. And if the controlling team cannot manage that, do not waste the time of your procurement team for RM price forecasts. Upgrade your controlling team instead.


2) Anticipate RM price movements

May prices for commodities cannot be forecast, but there is a limited ability to scientifically anticipate the prices of many downstream raw materials.

There are at least 3 ways that RM prices can be predicted in the short term future, and these methods are worth investing in because they will extend your knowledge of the future P&L by up to 6 further months.


a) Develop cost-driver models for raw material to give you a 1-3 month outlook

Cost-driver models for your raw material categories will give you a 1-3 month outlook of your RM price movements

If you have done solid benchmarking of your products, and you have the statistical impact of price developments of your critical cost drivers of your raw materials, you can increase the predictability of your price developments in the future to 1-3 months from 50% to 80-90% certainty of the general direction of prices.

It is not the same as knowing whether a coin will land as heads or tails, but it is the same as rolling a dice and being able to call “anything but a 6”.

And 1-3 months may not seem like much, but that time is all you need to plan inventory, place orders, pre-condition customer on price increases, look for savings, etc. These 1-3 months are probably the best you are going to get, and it should not be wasted.

procureanalytiq procurement analytics

Here is an example of the type of analysis that ProcureAnalytiq enables you to model. Once you have established the correlation between the price of a raw material and a set of underlying cost-driver benchmarks, you will understand not only the correlation between the cost-driver but also the time-lag.

In this example the commodity is Naphtha prices and the raw material is a downstream product dependent for part of its cost on Naphtha. The time lag between the Naphtha price and the raw material is 4 months and the correlation is 74%. This means that any price movement of Naphtha has a 74% likelihood of predicting the price change in your raw material prices 4 months later.

That is not the same as knowing. But it is also not the same as flipping a coin. And it is the kind of information you have to have.


b) Use future price contacts to extend the 1-3 month outlook to 3-6 months

There are methods to stretch the 1-3 months outlook of your prices to 3-6 months outlook for your prices, which is to take the future price contracts of the major cost drivers as an indicator of the price trend for the critical cost drivers.

The 3-6 month outlook starts to build in more than just the supply side into the equation – they start to include the supply-demand balance into the numbers which is highly valuable information.

Of course future price agreements and market-spot rates may still diverge significantly, because market events may impact them, but the future price contracts are still likely to be a good indication of future price behaviour because they are based on the current imbalance.

Using those future price predictions in your cost-driver models is like to give you an outlook that is 60%-70% certain of predicting price trend relatively accurately.

procureanalytiq procurement analytics

Above is an example from ProcureAnalytiq tool. A normal outlook may give the impression that the prices are likely to decrease. An outlook including the future price contracts may give a reflection and a warning that there is risk of increases as well.

There are actions you can take to make those 1-6 month outlooks more likely and more accurate.


c) Implement price mechanisms and/or formula pricing

If the supplier is open to it, and you want to eliminate more uncertainty, it is possible to build a price agreement with your supplier that is based, in part, on the price movements of key cost drivers such as feed-stock, market benchmarks, FX rates and/or agreed cost down targets.

Implement a formula pricing structure based on certain critical feed-stock, FX rates or other measures eliminates risk for both parties in the relationship. I am not a fan to make it legally binding so you can always leave room for discussion

This will not extend the outlook for price movement beyond 1-3 months, but will increase the likelihood it will happen. And it will therefore reduce risk.

The ProcureAnalytiq system was built not only to establish correlations and forecasts but also to help a supplier and customer to track and implement a formula pricing system by tracking agreed benchmarks, and providing commodity price data as input. Price mechanisms or formula pricing, the risk and opportunity, will be the subject of a future post, but in ProcureAnalytiq it looks like this:

procureanalytiq procurement analytics

d) Hedge RM price and FX risk

You may be able to hedge some basic commodities through derivatives. Personally i am no fan of hedging, partly because it costs money and is a non-core skill and partly because for so many products you cannot find a suitable hedge. Nevertheless, if you stakeholders prefer less volatility in results then it may be a worthwhile action to take.

However, if you have significant FX exposure to a single currency then that risk should be hedged in the short term to avoid major profit volatility.

Build business processes and system that can cope with, or even exploit, market volatility

To eliminate uncertainty on your results, the most important action is also the most complicated.

To build an organisation with processes and systems that can:
– Clearly identify significant changes in prices as early as possible
– Understand the implications of those changes quickly
– Have processes to help make the right short-term decisions
– Make the information transparent and actionable for the whole organisation

To have a transparent, alert and flexible organisation in volatile times is the only action likely to give your business a sustainable competitive edge in the longer run. I described some of these actions in last weeks post.

In summary

In summary, please do not waste your time on long-term forecasting of RM. Anything beyond 6 months cannot be relied on. 

Instead build scientific and analytical models to improve the likelihood of the outlook for 1-6 months. Beyond that, forecast a straight-line and build a business that can cope with volatility. 

And ensure your controllers have a good grip on the impact of current price agreements, and the short-term RM price indications, on the future P&L. It will give you an accurate Profit & Loss outlook for the coming 12 months.

And, of course, the team at ProcureAnalytiq are available to support you with this!

Procure Analytiq


ProcureAnalytiq is an online cloud-based software tool to track market developments and leading indicators related the direct material purchases for your business. 

ProcureAnalytiq enables user to faster reaction to market changes, better negotiations, automated forecasting of material pricing, better internal and external communication, and ultimately reduces direct Raw Material prices.

Interested to explore more?  



ProcureAnalytiq enables external benchmarking of your raw material pricing

ProcureAnalytiq was built to support tracking critical benchmark and cost-driver price development against your RM pricing.

Track your pricing against  external benchmarks

Finding and tracking external benchmarks is a critical requirement in procurement. It requires advanced search for external benchmarks and system to ensure that the tracking is correctly done in terms of Indexing, FX, Unit of Measure,

Track your pricing against critical feed-stock pricing & disruption

Choosing the right data sources for the critical cost drivers and proving the correlation through a look at history. Many procurement managers already keep an eye on 1-2 critical cost drivers. But often they are searching for the right price trends and they may choosing the wrong source of cost-driver data leading them to reach the wrong conclusion.

Build price indexes which are an indicator for your business or SBU’s

ProcureAnalytiq enables you to set up benchmark indicators in minutes to establish overall market indicators for your industry.

Save time & effort in procurement

In addition, the search of data as well as model building in Excel takes times and effort by the procurement staff. This time is better spent on interpreting data and planning negotiations rather than fiddling around in Excel?

Sharing of results

ProcureAnalytiq helps users to share their analysis over time, so that only 1 junior person can maintain the data (based on reliable data sources) and the others can use the analysis for interpretation and communication. It also allows a team to share their input with the supervisor or with research or other business partners.


Interested to explore the topic futher?

If you are curious about the topic of price benchmarking, especially of critical cost-drivers, please feel free to reach out to me through the Explore ProcureAnalytiq page


Price index introduction

Price index use cases

Price index tools