Antony Fisher of spend intelligence specialists, Mintec, explains how cost modelling can generate real advantage for procurement professionals.
In a world of fake news, it’s easy for procurement people to make assumptions and take things for granted. But imagine if we knew exactly what it costs our suppliers to manufacture something or provide a service. Negotiation would be simple as we would understand exactly where to aim.
If we also knew how prices would change over time we could work out when to buy or sell. Some people have spent lifetimes trying to figure this out. Imagine if we could do it that easily.
Well, actually, we can. The process, known as cost modeling, looks at the components that go together to make something, figures out what the cost should be and then compares it.
To really get behind prices and costs in this way, we need to hone our detective skills.
Take, for example, your favorite can of soft drink for a leading brand. What do you think it costs to produce that can? Obviously that information isn’t published. But if we look at what goes into making a can of soft drink, we can work out that it’s probably about 40 to 50 cents, including all the marketing, shipping, and distribution. Clearly, there is quite a bit of profit in the soft drinks industry.
What about a leading smartphone brand? People have figured this out and it’s estimated to cost about $150 to $200 to manufacture. That’s a long way from what we pay for one.
In scenarios such as these, understanding the cost makeup doesn’t really help. When buying a brand, the price point will be set at wherever the manufacturer needs it to be. But if we’re purchasing, for instance, cleaning services, we can ascertain how many hours and what materials go into that. Or if we’re in the business of, say, baking bread, brewing beer, or making pizza, there are distinct ingredients to consider, and we can develop cost models.
This situation is amplified when considering non-branded products such as private label or contract manufacturer products where margins are much slimmer. For businesses associated with their manufacture and sale, the fluctuating cost of ingredients has a significant impact on the cost of goods sold or COGS. Getting it wrong here can mean the difference between a profit and a loss. This can hurt when you consider the volumes many of these products are produced in and the speed at which they move through the supply chain.
At Mintec we cover around 14,000 items and big shifts can occur in the price of raw materials.
Take rapeseed oil, which has recently become very popular. Back in April 2020, the price sat at about £600 per metric ton. Fast forward to January 2021 and it leapt to £800 a ton. People will ask, why? Major reasons behind its popularity include an increase in demand for a product lower in saturated fats than something like palm oil. Also, demand is further boosted due to its use in bio diesel. Production capacity can also make a huge difference. Around 35 million tons of rapeseed oil are produced each year, whereas the figure for palm oil is around 70 million.
When procurement teams look to negotiate, they will generally track a range of products. Knowing what’s happening, and what has happened with a product, can give a sense of direction and an understanding of how major factors, such as the weather, have affected it.
Intelligence can really strengthen a negotiating position. But how do you get this valuable data?
Since the early 1980s, Mintec has built huge levels of information. There are several ways of collecting it. A lot comes from future commodity trading. Data from bodies like the Chicago Board of Trade or the London Metal Exchange can be tracked using our platform. We also have information from government sources and a team that works with proprietary data, speaking to producers about specific products. All the information is then aggregated on our platform which allows our clients to see what’s happening.
Modelling in Practice
Consider setting up a pizzeria, using ingredients such as flour, yeast, cheese, chopped tomatoes, onions, mushrooms, peppers, and herbs.
The business will also need premises, water, energy, kitchen equipment and, of course, a pizza oven. There are numerous areas of spend.
Now, we can only sell our pizzas at a certain price point. And we want to make a profit. So, knowing the cost of what we’re buying is important, including what we need to pay our suppliers and what it means if the price of raw materials is likely to change.
In building a cost model, the first thing is the makeup of a product. What goes into it? So, we would look at the recipe, take individual components and use the raw material blending function in our platform to add them together, using the relevant percentages. This would generate a trend as to what’s going on. To understand the future, we consider what’s happened before, what’s happening now and major areas that could affect it.
Cost modelling is, basically, taking different bits of information about those ingredients and connecting them.
We can choose how much detail to apply. Taking tomatoes as an example, consider where they come from. Italy is a big producer but so are Spain and Portugal. Knowing this will help determine the most accurate picture.
Predicting the Future
We are looking at different ways of putting predictions into our tool. It is always interesting to look back and see what’s happened with a product. If it’s at a very high price, a procurement team will probably look at short-term buying. If something is at a five-year low, they might decide to lock in the price for as long as they can.
I love the concept of prediction, but so many variables exist in the world. Say, for example, we wake up tomorrow facing a global shortage of cheese.
Preparing for Scenarios
How can we better prepare for scenarios that are around the corner?
Weather is probably the biggest factor. Our team of analysts investigate markets and report on what is happening around the globe. They look at production, consumption, and likely shortages of products. That allows clients to see possible pinch points.
In 2015-16, I worked with a client using our platform to look at canned baked beans. By analyzing the period of their last contract, they could show how much the price had moved. They renegotiated and received a refund of around £2million!
Big data involves extremely large sets of data being pulled into one place. With 24-hour access through smartphones and tablets, you could almost end up with too much information. But it is good to have data from different sources to make informed decisions based on facts.
These facts can be used in negotiations. Our platform will bring up a price for an Egyptian onion, for example, and show the market movement in a few seconds. For procurement teams, there is skill in being able to make choices at the right time to benefit a business. Obviously, if wrong, it could also cost a large amount.
Going forward, we will see more amalgamation of data into in-house systems. We have the ability to feed our data straight into a company’s platform so they can see the market price alongside what they’re paying and do the analysis themselves.
I think we will move on beyond these stages and get better at predictions using big data from numerous sources.
So now and in the future, whether your business makes pizzas, builds aircraft, or even sells services, quality intelligence will strengthen your negotiating power and generate real competitive advantage.
Written by Antony Fisher, head of data acquisition for Mintec, the world’s leading independent provider of prices and analysis covering more than 14,000 food ingredients and non-food raw materials.
Positive have formed a collaborative partnership with Mintec to enable procurement teams to access a unique set of data, resources, and analysis across a wide range of raw materials and commodities. This, alongside the best-in-class strategic procurement workflow, toolkits and learning academy, provides a new approach to deliver game-changing results.