We all know that the future holds surprises. We just don’t know whether they will be good or bad for business. The further one looks into the future the fuzzier the picture gets. At some point, so-called forecasts aren’t much better than guesses. Nevertheless, Andrew Hill believes that, because distant forecasting is difficult, too many companies (to their detriment) ignore looking into their long-range future. [“Look into the future before it is too late,” Financial Times, 7 May 2012] Hill asserts that businesses need to “be able to scan the horizon, 10, 15 or even 25 years ahead.” Hill continues:
“How is this state of vigilance best achieved? The classic big company model is to delegate the blue-sky thinking to a unit at headquarters. Royal Dutch Shell’s 15-person global business environment unit, which generously publishes summaries of its long-range scenarios, looks typical. GlaxoSmithKline operates a sort of think-tank looking at the scientific developments likely to shake Big Pharma, 15 or more years from now. (Take it as read, by the way, that any industry with ‘Big’ in its popular nickname – Big Oil, Big Auto, Big Pharma – needs to do some futurology as an antidote to the complacency that is a side-effect of elephantine corporate size.)”
I agree with Hill that the larger the business the more important it is to look further into the future for both risks and opportunities. As I noted earlier, the further out one looks the fuzzier the picture becomes. That is why the Royal Dutch Shell team offers ups “scenarios” and GlaxoSmithKline looks at how trends might affect the future. Neither team really does forecasting. Hill writes, “Both these arrangements are less traditional and, critically, less static and more open to external influence than they might look.” He continues:
“The Shell unit, for example, is the core of an interactive network that, in constructing any one scenario, could build in the views of 150 operational specialists at the company and up to 250 outsiders. When the reports appear, the idea is that the main assumptions have already been communicated to, and discussed with, senior executives. At GSK, the think-tank is chaired by Moncef Slaoui, the group’s well-regarded head of research and development. His horizon-scanners include internal and external experts. But he also has responsibility for weaving shorter-range developments into the business model. At Infosys, scenario planning is part of a five-year rolling prediction process. Its outlook is shorter-range than the pharmaceutical or energy industries, but then, as [S.D. Shibulal, new chief executive of India’s Infosys,] told me last week, ’10 years is a long time in IT’.”
Shibulal makes an excellent point. You need to know your industry and the speed of change that occurs within it. Hill insists that long-term forecasting (or scenario evaluation) is only worth the effort if corporate executives are willing to listen and act. He writes, “Future scenarios can give senior executives what the Shell team calls ‘memories of the future’, which will be triggered at the first sign of predicted changes.” That is the critical moment, Hill insists, when decisive leaders must be “prepared to risk unmooring their companies from the past in the interest of future survival.” He concludes:
“Fortune-telling is a thankless task. But unless boards act before insights crystallize into hard reality, I predict that even the cleverest forecasting unit will quickly become an ‘I-told-you-so’ department, staffed by embittered Cassandras.”
The horizon for most corporate forecasting is much shorter than the timeframes discussed by Hill. The forecasts (be they daily, weekly, monthly or annually) are an important part of the sales and operations planning process. Lora Cecere told the editorial staff at SupplyChainBrain, however, that many forecasting teams have a built-in bias depending on to which organization they report. She insists that a forecasting team “needs to report to an organization that’s neutral.” [“Revamping the Organization for Forecast Excellence,” 8 May 2012] The article continues:
“The highest degree of bias and error occurs when forecasting reports to sales, which is responsible for volume. The second-highest is when the discipline is controlled by marketing, which oversees growth and market share. The third is when the target is manufacturing. The ideal home for forecasting, says Cecere, is a profit-center manager, finance or corporate strategy function – ‘someone looking across the corporation, not just at vertical silos.'”
Forecasting provides another example of why corporate silos are bad for business. Cecere laments the fact that forecasting teams reporting to a neutral organization “is more the exception than the rule in organizations today.” The article concludes:
“It’s tough to wrest control of the forecast from sales, she acknowledges. One reason is that sales has a natural bias for error, often based on an incentive structure. In a recession, however, it’s more important than ever for companies to be ‘market-driven,’ sensitive to what’s really going on among the customer base. The latency of critical data can be as high as two or three months, making it difficult for companies to respond to true market conditions. Businesses need to take a close look at system bias and error. ‘Supply chains with high error should be designed for agility and responsiveness,’ Cecere says. ‘Those with low error should design for efficiency.’ Accurate forecasts should be encouraged and rewarded, in the form of better prices for customers. At the same time, the company needs to take responsibility for improving the forecast it conveys to upstream contract manufacturers. ‘Forecast accuracy is one of the largest waste areas of the supply chain,’ Cecere says. In the wake of the recession, ‘we’re now seeing people looking at accuracy as a determinant of good relationships.'”
This was not the first time that Cecere has done an interview on the subject of forecasting with the folks at SupplyChainBrain. In an interview conducted last summer, Cecere told the SCB staff, “You can’t hedge against rising commodity prices, work successfully with contract manufacturers or excel in so many other areas without forecast accuracy.” [“What Drives Forecast Excellence,” 5 August 2011] Cecere told the SCB staff that there are “five drivers of forecasting” as well as “seven sins of the process.” The five drivers are:
“[First,] you have to have leadership that is every bit as committed as executives are at the company you’re patterning after. Second, to drive forecast improvement, you need to implement forecast value-added analysis. That’s a continuous program, not just a one-time project. Three, understand what is driving your market and determine how to stay in touch with that. Four, educate your executives, many of whom ‘grew up’ when supply chain planning was in its infancy and haven’t kept up with its advances. And five, you have to ‘own’ the entire forecast. You have to consider not just production, but pricing, promotions, product launch and other factors.”
Hill and Cecere agree that, regardless of the forecast timeframe, leadership is critical to making the process meaningful. Cecere’s seven forecasting process sins are:
“The first is the failure to forecast what you should sell. Two, not being careful enough to implement forecasting as part of the demand plan. Three, not having accountability in your processes. Four, failing to ensure that prospective partners indeed have the capability to collaborate and not just the aspiration. Five, not matching the rhythm of your forecasting with the rhythm of your supply chain. Six, failing to fully use your system, including forecast valued-added analysis. And finally, the ‘most deadly’ sin is not believing in forecasting.”
The article concluded:
“With commodity prices going up, with unrelenting demands to maintain growth and with the need to continually introduce new products, forecasting matters more than ever, says Cecere. In addition, supply chains are much longer today, capacity may go to the highest bidder and contract manufacturers often base their pricing on the accuracy of one’s forecasting. ‘So, you really can’t play today.’ Does benchmarking against acknowledged leaders guarantee success? Well, it helps, but of course you have to measure yourself against a like company, one with a supply chain or supply chains much like yours.”
Martin Buckley appears to be in agreement with both Hill and Cecere when it comes to the importance of forecasting (both short-, medium-, and long-term). He writes that companies make a big mistake when “the forecast is seen primarily as a budgeting and financial tool.” When such a view prevails, the forecast “it is not maintained and utilized to its full potential throughout the year to anticipate customer demand and reduce lead times and inventory.” [“The importance of a long range, continuous forecast process,” The 21st Century Supply Chain, 22 September 2012] Buckley continues:
“The question is, how can this situation be improved? The answer is: forecasting should be viewed as an important tool in meeting corporate goals for growth and profitability, not just as a budget exercise. In order to leverage forecasting as a vital asset to the enterprise, following issues need to be addressed:
- Forecasts are a dynamic variable, so they can change significantly over even a short period of time. This means the forecast process needs to be much more frequent than annually, preferably monthly. …
- Forecasts should cover your longest lead time items, in order to properly anticipate demand and not be caught short. This means forecasts need to roll forward, covering the full length of the demand horizon at any point in time.
- In order to support a more frequent forecasting cycle and improve accuracy, the forecast must be streamlined and easy to use. A forecast which takes a month to prepare is already out of date by the time it is released.
- The forecasting process must be viewed as integral and important tool in the overall functions of the company. The people generating the forecast must be aware of its importance to the strategic interests of the enterprise. …
“Having an accurate, regularly updated, long range forecast to provide guidance to the supply chain is more important than ever. A tool which can quickly and easily supply such a forecast is a must, as is a process to provide feedback on forecast assumptions to enable corrective action to keep the enterprise on track.”
New technology can help as well. Predictive analytics is another tool in the forecasting kit that can complement operational and historical data to generate more accurate (and, therefore, more useful) forecasts. But that’s a topic for another day.
