IndustryWeek’s Manufacturing Business Challenge this month is entitled “Unreliable sales projections ripple through company.” This month’s challenge focuses on a company struggling with faulty forecasts. The challenge is:
Since I’ve been the CFO at Sodtt Ceramics the last two-plus years, I have worked to develop a thorough sales and operations planning process that monthly works through plans for sales, production capacities, inventory, lead times, investments, finances, etc. Sodtt makes insulators and substrates for the electronics industry as well as orifices and nozzles for industrial uses. With such a range of customers, it’s important that our planning works as planned. Occasionally, everything hums along just fine from month to month, but inevitably we are blindsided.
I believe good organizational planning really starts and ends with our customers and sales forecasting, and too often this data turns out to be very unreliable. The director of sales and I have tried to install some standardization to the sales function, from the way salespeople define “a sale” to the manner by which they develop their individual forecasts. But most of the sales staff are a bunch of cowboys, shooting from the hip and grabbing their commissions (forecasts be damned). And despite some investments in demand planning and supply-chain planning tools, as a company we still rely heavily on a variety of manual techniques and legacy spreadsheets to pull our forecasts together and share. And these homegrown tools make it difficult to update the many day-to-day changes that occur.
I believe the sales forecasting component of our planning process has turned into Sodtt’s Achilles heel. With the rapid ups and downs of our markets today, my operations and supply chain is constantly being whipped back and forth: either piling up unnecessary inventories (ours and suppliers’), overtime, and expediting costs to hit sales targets that eventually don’t materialize, or straining to satisfy unexpected orders and racking up every conceivable quality and delivery error in the rush. I don’t want a crystal ball, but I do need to reorganize our sales forecasting before it damages the company. Where to begin?
Solutions to this challenge are provided by Deloitte and Kinaxis.
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Tags: Forecasting, Sales & operations planning (S&OP)
Posted in Demand management, Sales & operations planning (S&OP)
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I too have experienced similar type issues in my professional career and it shows the inherit weakness of the S&OP process if the right people aren’t assigned the responsibility (this means monitory) for actively participating in the S&OP process. I don’t mean simply bonus and commissions but performance evaluations as well.
I really believe that we have the wrong dialog of discussions going on between supplier and customer. Our cowboys in sales are doing what they do best, selling ongoing items and new products into the customer. That is what they are paid to do. Our sales teams should be involved in the product requirements of our customers as far as the choice of items required and the possible retail set locations but not of the inventory requirements of our customers.
Too often lines of communication between the supplier and the customer aren’t open up enough to receive the information really needed to successfully develop demand plans. This means we need to have a portal into our customers inventory levels. This should be done electronically or any way available, but data is key and he who has the most data wins in the end. When we understand the inventory availability of our customers, we as inventory managers, should be able to develop ongoing plans to support the customers without whipping the rest of our supply chain back and forth.
I would begin by working with your sales team to get access to the inventory managers of your customers and developing a form of communications company to company. This may be through EDI transactions or entry into their system. Develop a VMI process with your customers so they have incentive to work cooperatively with you. This may require some additional staffing on your part but the savings received from stopping of the whipping of your organization will easily offset these modest cost.
I recognize much of the statements you make. In times like this, a good S&OP process is critical to keep service levels up and inventory levels down, however the demand process itself is much more difficult since market behaviour is much harder to predict and the bullwhip effect presents itself from it’s meanest side. Solutions however are not necessarily on the system side; much can be done on the organisational-communicational side.Spending more time on the actual demand planning with acceptance that the forecast error is going to be larger than usual can keep your output closer to reality, maintaining an appropiate service level while keeping inventory levels acceptable. Decisions you can make is to partly detach your supply planning from your forecasting if the forecast errors are too large, keeping production more stable. While running the risk of lower service levels, you filter out the short term fluctuations of forecast which can be devestating for your supply chain, inventory wise and capacity wise by demanding huge flexibility which often cannot be delivered anyway (or with high supply chain costs, not always visible at the time of releasing your plan). Portfolio differentiation important her to get the best of both worlds: Which products am I going to handle which waydepends on the actual market predictability and the flexibility that can be offered on the supply side.
This is just one thing you can do; there are many, many more actions you can take on the short term (like increasing your forecast cycle for some products) and longer term (creating more pull on the supply side). However, this box is pretty small so I leave it as this.
Having worked with a number of companies over the years, this issue of synchronizing sales foecast to material flow and actual demand is prevelent in almost every business sector in which I have been associated. It is a major stumbling ground for all businesses and may be the difference between complete success or failure as a company in the market place. All of the tactics and strategies that have been discussed in associated articals recently published in this venue certainly need to be working someplace in the organization. Not inclusively, strategies such as seamless movement of materials through the supply chain, lead time reduction, customer and supplier collaboration, forecast rationalization and frequency of review, approved forecasted plan loaded for overall implementation and material flow converted to demand driven replenishment techniques all play a major role and someone in each organization should be charged with fine tuning these strategies to the companies overall goals. Some of these strtegies are more conceptual in nature and may cost little or nothing to implement other than some training or software development while others such as flow strategy, lead time reduction, core competency review, and design for manufacturability etc. may require significant capital expenditure to right size a company to it’s market.
The one thing that has not been discussed in many of these articals is competency of senior managers in charge of these given areas, i.e. Supply Chain, Manufacturing, Sales and Marketing, Finance, and the senior executive all alike. It’s way to easy in a corporate atmospher for these people to shirk their responsibilities or delegate to lower levels then squak about the end result. This small group of people should be the driving force toward implementing the processes mentioned, doing trial and error studies on how specific practices fit into the organization and making sure that the proper practices are implemented. Invariably we all know forecasts are going to be wrong, we know to some degree that error is going to drive ripple effects through the organization and supply chain and we know someone in senior management is going to squak about that error. It is however, the rare company indeed where the few senior executives in charge stand up to the line agree totally on a strategy, put the stake in the ground say this is the direction we are going to take, and then take responsibility for that direction.
I can relate to the problems you are facing randy. As Marc mentioned, you are facing a classic case of the bull-whip effect. The key here is to communicate more openly with your customers – never easy given deeply ingrained behaviours and industry norms of not sharing data openly.
Your clarity on not looking for a crystal ball in the shape of a sexy forecasting algorithm is encouraging because that won’t take away your woes. Visibility into downstream inventories is a solution and given the nature of you customers, who themselves are businesses, you will end up with data one step closer to the end-user of the final product which means lower forecast variability and proportionally lower inventory levels for Sodtt.
On the behavioural side have you ever considered measuring and incenting your sales people on forecast accuracy. All it would take is to put in place an error measurement process using a measure like mean absolute percentage error (which takes into account both under and over forecasting) and starting with a level of accuracy that the best saleman in your company exhibits. The eventual goal is a industry-best/world-class %age. Bonuses and even commissions can be aligned to this one simple (with total sales buy-in) measure. The key remains in striking a balance between commissions on maximizing sales as well as for more robust and relaibale predictions. In the longer run you can work with your customers to get as much retail data for your derived demand suplly chain.
One very important factor to keep in mind is that your need different supply chain designs for different products in your portfolio. This will be indicated by your greater ability to forecast certain product ranges than others. Your complete S&OP process will have to be customized around this product heterogenity. With predictability comes efficiency while wide swings in forecast demand a more demand-driven and resposive supply design.
There is no one quick fix to this problem. Adjusting the above levers will take yo in the right direction.
Best of luck.
This is a VERY old problem the root cause problem of which has not been addressed, so it is not fixed. Sales people want to make sure their customers are not delayed in getting their orders fulfilled and operations wants minimum inventory based on pressure from finance to keep inventory low. The variable is the customer who won’t cooperate since they think their problems are your problems.
I addressed this issue with what I think is a relevant solution. You can read my paper, “Whose Forecast is It Anyway?” free at http://www.customermanufacturing.com/free/mktgmgmt.shtml.
Mitch
Most companies are run by CEO’s with a Sales/Marketing background.
Your issues fall on deaf ears. They will only listen to you when the inventory is out of control.
Keep good historical data so you will be able to defend yourself.
John – you’re absolutely right, and I think as you’ve accurately noted that means the company emphasizes sales excellence over operational excellence. I do believe, and AMR at least has commented on this as well, that this is slowly changing. I’ve seen evidence that more supply chain executives are at least gaining a bigger seat at the table. I think we have a long way to go, but I do sense there’s a growing, if still too small, recognition as to the strategic impact that supply chain excellence has on both the top and bottom lines.
As Ron pointed out tackling this problem may well be the difference between success and failure. Unfortunately as others have noted there is no silver bullet. There are steps to take, all of which are noted in other comments.
It needs to start with leadership. Easier said than done! There is not enough space here to talk about it but check out Hoshin Planning as a way for senior management to help steer a business towards it’s vision by providing focus and alignment. This will help break down the barriers in your S&OP process so all participants have visibility outside of their silos.
As Rich stated, getting closer to customers and suppliers will also be critical in tackling the problem. Point of sale data is becoming the norm versus historical data. Being closer to the outside participants will also enable you to know sooner anything that may throw your strategy out of alignment. It will continue to be important to collect all inputs from sales, marketing, product management etc. and quickly rationalize these numbers to drive to a strategy you will execute on.
Finally as Marc pointed out there are all the improvements that are driven by Lean Thinking (this is also in Mitchell’s white paper), leadtime reduction, pull based replenishment, and the list goes on. Easy to see why this is one Industry Week’s toughest challenge.
There are many good ideas mentioned, and they all have a role in improving an organisation. I am wondering though whether any will directly address the problem. Most of the responses address problem areas within an organisation, but to find cause and effect you have to extend beyond these borders, into the area of supply chain.
I haven’t seen anyone talk about the “Bullwhip effect” You can forecast this problem to death, but without a relatively stable or predictable demand – forecasting won’t solve this problem. Forecasting works when, as the writer suggests the demand is fairly predictable.
The further away from the actual demand (end user) the organisation is the greater the effect of the deviation in demand will have on the organisation. Like the impact from a tsunami felt hundreds of miles away as the variation in the size of the wave picks up more ‘inventory’ alond the way from where the cause occured.
Forecasting in situations where high demand variability occurs, will not deliver the desired results, and the less relaible they are, the less effort people will use to do them and to work with them. And they more they rely on ’shooting-from-the-hip’ and manual systems. It doesn’t mean they (forecasts) should be discarded completely, but understand the demand variability tolerance levels that they remain useful.
Identify the products that fall into this acceptable tolerance and forecast these to start with. For the others use a different stategy. Consider changing these to demand driven products.
Get closer to understanding the ‘real’ demand and get into discussions with your immediate customer and understand where they are building their own ‘protection’ by adding to and magnifying the variability. Increase reliability on the products that you can forecast, and keep working with your customer to reduce the leadtime, and get more visibility for the demand driven products.
Research the bullwhip effect, research Collaborative Forecasting, Planning, and Replenishment (CPFR) – (there is a book by Ron Ireland on this). Find the Walmart and other case studies on this and get some practical advice on how to go about reducing the bullwhip effect. http://www.vics.org/committees/cpfr/ There is help out there if you just know where to look for it.
Other resources: Supply Chain Council, APICS
Tracy – all excellent suggestions. I’ve seen many companies do exactly what you’re suggesting. The one area that I definitely see getting more attention these days is in collaborative “co-planning” – where you identify your largest customers and build processes to more directly collaborate on what true demand is going to look like.
I think one of the key takeaways here is that this isn’t a “cookie cutter” approach – that is, the same approach doesn’t apply universally to all aspects of the business. Different strategies need to be employed depending on the nature of the products.
Great suggestions and thanks for sharing the additional resources.
There are lots of really good suggestions in the comments for improving the success of your S&OP process. As Randy says, it’s not going to be a ‘one size fits all’ solution. Even if the situation is as bad as John Keane suggests and you’ve resorted to relying on good record keeping to keep you out of trouble, you’ll still have to have some suggestions ready on how to improve the process if/when senior management gets tired of dealing with the same problems during every planning cycle. I think the following are some realistic measures that any company could take to address some of the issues raised in the Business Challenge.
Most companies have a range of products and customers. You may not be in the situation where 80% of the your revenue comes from 20% of your products/customers, but I believe that going through a product/customer segmentation exercise should be quite easy to do and will help you focus on where to spend most of your process improvement resources. For each of the key segments, measure the demand variability and decide where your cutoff is.
If a segment is determined to be too variable, focus on supply-side resolutions such as make-to-order, postponement/inventory optimization, and safety stock.
If there is a manageable amount of variability, focus on forecasting improvements such as collaborative customer forecasting and collecting customer demand inputs (e.g. POS). If you feel it’s possible to reform the sales group, start engaging them in discussions using the accuracy metrics that you are collecting such as bias and at least get a sense of root causes of the inaccuracies. Also, if you and the sales director feel that sales input is ultimately key to improving the process, brainstorm possible approaches to incenting the sales group to improve their accuracy.
And of course, you have to have the right tools; one that don’t require alot of manual data maintenance and steep learning curves. There’s nothing worse than trying to promote a good process using bad tools.
Customer segmentation, as Bob suggests above, is a one way to analyze the demand. Adding profitability to the customer segmentation also helps in focussing the attention on where it makes sense to improve.
HP developed a system for dealing with supply variability more than 10 years ago which can be applied to the demand side too. HP evaluated supply requirements for all bought components to determine the minimum and maximum demand over a period, which I believe was a month. By using longer periods, such as a year, one gets an idea of average demand.
- For commodity components, long term contracts were set up to satisfy the minimum demand, greatly reducing the inventory liability risk, while increasing the supply shortage risk. However, because the components in this category are commodities, the real supply shortage risk is low.
- For critical components, especially those with associated supply risk such as single sourcing or high revenue consequences, long term contracts were set up to to satisfy the maximum demand, greatly reducing the supply shortage risk, but increasing the inventory liability risk.
- For components between the 2 categories above, long term contracts can be entered into for the average demand, thereby straddling the issues of supply shortage and inventory liability risk.
This way of looking at the problem can be applied ot the demand side too. For example, the majority of the demand variability may come from single customer or region. Different inventory or order policies can be adopted for the region in which the demand volatility occurs. If the demand volatility is across all demand locations, then low cost manufacturing capabilities, probably outsources to low cost countries can be used to satisfy the average demand, while flexible, higher cost manufacturing can be used locally to satisfy the peak demand.
Bob May hits the root cause of the problem: untrustworthy sales forecasts.
“If you feel it’s possible to reform the sales group, start engaging them in discussions using the accuracy metrics that you are collecting such as bias and at least get a sense of root causes of the inaccuracies. Also, if you and the sales director feel that sales input is ultimately key to improving the process, brainstorm possible approaches to incenting the sales group to improve their accuracy.”
If that’s the root cause, why not fix it, rather than just focus on working around it? Problems in this area always revolve around people, processes and technology.
- People: yes, sales people can be cowboys, but the most successful ones tend to be more thoughtful and process-oriented (I believe these are the ones that end up as CEOs!). Sales people deal with very subjective data. Not only do they have bias, but their customers have biases, constantly changing purchasing needs, and economic and competitive issues that whipsaw their buying needs. A key to getting a good sales forecast is capturing these changes as they happen, and having the most complete data set you can get. It’s not necessarily about having the the most accurate forecast data, but when you have sales forecast data to look at, you can understand biases, accuracy, consistency and completeness. Then the sales forecast can be intelligently vetted and adjusted to create a predictable sales forecast in time to allow the supply chain to react. This turns the subjective data that sales works with into objective data the rest of the company can act on.
- Processes: the processes around sales forecasting are very different than supply chain. Sales forecasting is typically a tedious, time-consuming pain with error-prone Excel spreadsheets that take forever to roll up. Trying to find the major trends in expected customer demand (like the recent volatility) much less the details (like I have a new competitor in a single region that is underpricing me) that need action is pretty much impossible. For this reason, most companies attempt to run a sales forecast much less frequently than it should be run. A monthly or quarterly forecasting exercise that takes weeks to roll up is completely inadequate today.
- Technology: the aforementioned Excel-based process is often augmented by sales with attempts at forecasting in CRM (which doesn’t handle product forecasts over time, only opportunities), or homegrown applications. Imagine if you were trying to run your supply chain on spreadsheets, without the systems support you now have! What is needed is a purpose-built sales forecasting application that makes it easy to capture all the sales forecast because the sales team uses it. It needs to roll up the forecast continually to provide a complete view. It also needs analytics that help sales management to pinpoint both big trends and little details that need attention, and properly vet the sales forecast. Only then will sales be able to provide a trusted and actionable sales forecast to the rest of the company.
It seems to me that fixing the root cause will only help smooth the whipsaw effect experienced by the S&OP parts of the company.