Part V: Demand Projection and Demand Management: A Basis for Cost Avoidance | Sievo

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Part V: Demand Projection and Demand Management: A Basis for Cost Avoidance

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Thought-Leadership Piece

In this 6-part series, guest blog writer Michael Lamoureux, a freelance procurement expert, explores and takes a deep dive into spend forecasting. With years of deep domain craft in sourcing and supply chain, he shares the secrets of what it takes to keep up in today’s fast moving economy. Read Part 1, Part 2, Part 3Part 4, Part 6.

In our last entry in the series, we dove into should cost modelling and explained how the use of analytics with should cost modelling could identify cost saving opportunities “under the covers”.  But that’s not the only opportunity for identifying spend reduction opportunities.  Another is better demand management.

The reality is every dollar spent is a hard cost, and even if the dollar is spent on an item for resale, that dollar is a lost dollar until such time as the item is sold for an amount greater than its total cost and the dollars are collected.  And if it’s an item for use, that dollar is gone, so the company better realize the value on that dollar spent (which, generally, involves using the item to support business operations).

Thus, in order for the organization to be practicing good spend management, it’s paramount that it only buys items it will actually use or sell, and not too long before those items are actually used or sold.  In the case of inventory, buying 10 widgets needed to maintain the production line “because you get 50% off for buying ten” is not a great use of cash if, on average, the widget only has to be replaced twice a year and the widget happens to cost $10,000 a unit.  Sure you save $25,000 now, but what’s the opportunity cost of not having that capital?  Added to the extra inventory cost of storing some parts for 5 years, which, even if they’re small, is still pricey when you consider the inventory has to be secure?  Added to the loss if the production line ends up being modified or replaced in three years to support the production of new products and the widgets end up becoming obsolete?

This is an example of where good demand projection, built on total cost of ownership models, would determine that the stock level for the widget should not exceed two, with a re-order of one unit being automatically made when the stock gets down to one (and only because there is a chance a part could be defective and wear out quicker than the expected 6 month utility timeframe and it typically takes a few weeks to get a new unit in).  The organization frees up 40K of cash for investment (in a resource to do analytics to find more savings opportunity) and essentially eliminates the obsolescence risk (as the organization would never have more than one spare on hand when a production line hit end of life).  Security would still be needed, but if the total inventory size, and value, is small (using a just-in-time MRO strategy across the board), the overall inventory cost would be less.

As should now be clear, the reality is that spend Forecasting is more than just cost forecasting, it’s also demand forecasting. But it’s not just about demand reduction, as in our widget example, it’s also about identifying demand growth early to gain volume leverage during negotiations or (e-)Auctions.  If you can project a new product is going to go from 100K units this year to 1M units next year, going to the market with a tender for 1M units will get you a lot more interest, and potential savings opportunities, than going to the market with a tender for 100K or 110K. If the product was new, and the organization only looked at year-over-year demand, it might see that demand for the less than one year old product was 100K, and use its rule of thumb.  But if it looked at month-over-month demand, it might see that demand was 5K, 10K, 20K, and 40K for the last four months of the year and see that the demand for the product was doubling.  It might then look at market size and similar trends in the past to see that the demand for products of this type levels out around 100K a month at peak, and stays at peak for about 9 months.  It could then project a demand of at least a Million units, and go to market with a much more enticing opportunity.

But demand projection and forecasting is not the only savings lever at your disposal — so is demand management.  Whereas demand forecasting really centres on identifying the right time to buy, and the right quantity to buy at a time (which is EOQ for you inventory managers), demand management focuses on reducing the total number of units needed, particularly when the item is a consumable.  (Generally speaking, the only times you want to reduce the quantity of goods for resale are when you want to end-of-life a product or it is just impossible to meet a greater demand due to raw material or factory production limits.)

While this is not always as straight-forward, and often requires situational analytics beyond just the data, it is quite possible with good analytics tools at your disposal.  The first step is to identify MRO / consumable categories where spend is increasing.  The next step is to figure out why.  Sometimes it will be spend you can’t do anything about.  For example, if the categories are cell phones and laptops, and every employee gets a cell phone and laptop, and headcount is increasing 30% year over year, cell phone and laptop spend are going to increase 30% year over year.  The best you can do is used the increased volume to negotiate a better deal.

But if the headcount is flat, and the paper and toner cartridge buy is doubling, and you are in the banking industry, the question is why?  Why are people printing so much?  If it’s because they are printing and sending more and more regulatory compliance reports and tax filings to authorities, then there might be an opportunity for reduction as most authorities now accept, or prefer, electronic filings, if the authorities don’t mandate it.  If the reason is because the online submission processes offered by the authorities are too onerous, then it might save the company a lot of money to subscribe to a SaaS service that makes it easy (as well as prepare the company for the time when online filings will be mandatory).  Forests could be saved.  If it’s because managers are still printing forms to have them filled out by applicants, maybe it’s time to invest in an easy tablet-based entry system where they can just hand a tablet to an applicant in a meeting which can collect all the info and an e-Signature.  More forests could be saved.  And if it’s because they are still printing out reports to compare different breakdowns, maybe it’s time to invest in a dual-display video card and second monitor for all employees who need it.  Even more forests could be saved.  And while there is an upfront cost to all of this, it won’t take long before the cost avoidance triples the one-time cost.  Paper is expensive, and toner ink is more expensive than oil or blood.  Think about it.  Carefully.

Good demand management also identifies MRO or consumable categories where demand is staying flat but costs are rising sharply relative to the demand.  Maybe the organization is using end-of-life technologies now supported by only a single supplier who is now capitalizing on the opportunity and doubling prices year over year due to the captive market.  In this case, the organization would save oodles, and avoid future cost increases, by switching to a newer technology.  Our production line example above that requires a $10,000 widget to maintain every six months is one example.  Another example is running the IT Centre on 8 year old servers that require older SATA 2 devices with integrated security options.  Even if the vendor told you they’d last 10 years when you bought them 8 years ago, at this point you should just upgrade … as the total purchase price would probably be the same as the annual maintenance cost.

But without good analytics, you’d never identify the categories where demand projection, or demand management, is key … and huge savings and cost avoidance opportunities would go undetected.

Hopefully by now you’ll see that when it comes to spend analytics, the top N opportunities identified by a canned report is only the tip of the iceberg — and most of the opportunities are below the surface, as with a real iceberg.  All you have to do is dive below the surface.


About the Guest Writer

Michael Lamoureux, aka the doctor, is the Editor-in-Chief of Sourcing Innovation (.com), a resource for sourcing, procurement, and supply chain professionals who are interested in improving themselves and the overall performance of their organizations. A regular contributor to Spend Matters, he is a Computer Science PhD who has been heavily involved in the Sourcing and Supply Chain Space since 2000 and the e-Commerce space since 1997. As a freelance procurement consultant with extensive expertise in sourcing, procurement, and supply chain processes, he aims to continually push innovation in and beyond the supply chain space. With particular expertise in analytics, modeling, and optimization, he is able to dive much deeper into technology and core issues, striving to help businesses with their internal knowledge transfer, positioning, and planning problems. 

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