Principles of the Master Cyclist

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“The brightest people in the world didn’t see [the recession] coming.” JOHN CHAMBERS, CEO, CISCO SYSTEMS INC.

“It was obvious the booming economic cycle couldn’t continue. We tightened our belts. We focused on cash flow.” RALP H LARSEN, CEO, JOHNSON & JOHNSON

As these two sharply contrasting views of the 2001 recession suggest, some managers seek to manage the business cycle proactively, while others deem it a pointless exercise. There is a similar divergence of opinion within academia. Many professors of both economics and finance believe that, like the stock market, the business cycle is a “random walk” that can’t be predicted — and therefore can’t be managed. Others believe that managers who carefully cultivate financial market literacy, who studiously follow leading economic indicators and who draw upon various forecasting models are likely to manage their companies better than their peers. I belong to that contrarian minority.

Prior to the 1980s, most economists viewed the business cycle as largely unsystematic and unpredictable. Since the 1980s, however, there have been numerous studies validating the predictive value of a number of leading economic indicators, including stock prices, the so-called “yield curve” and the Conference Board’s Composite Index of Leading Economic Indicators (an index that reflects both the yield curve and stock prices as well as eight other indicators).

Despite the existence of these studies, many academics still reject their findings and doggedly cling to the notion of a random walk business cycle. In this regard, stock prices remain a favorite butt of an almost 50-year-old quip from Nobel laureate Paul Samuelson that “the stock market has predicted nine of the last five recessions.” Nonetheless, at least some studies have found that stock prices have some predictive value, particularly when used in conjunction with the yield curve.

The yield curve — which measures the spread between short- and long-run Treasury securities — is perhaps most interesting from a managerial perspective. At any given point in time, the shape of the curve can be normal, flat, inverted or steep. An inverted yield curve has been historically quite accurate in predicting recessions, while the steep yield curve has been only slightly less accurate in predicting expansions.

The Index of Leading Indicators has been found to be at least somewhat useful in predicting movements in the business cycle. However, unlike the yield curve, it is more susceptible to generating “false positives” — signals that suggest a recession or expansion that, in fact, doesn’t materialize.

As for the various macroeconometric forecasting models, one of the more efficient ways for any executive team to use this (typically subscription-based) data is through the Blue Chip Consensus Forecast, an average of 50-plus monthly forecasts that, as a recent study found, “performs better than any individual forecaster.”

The point is that any manager interested in trying to better anticipate movements in the business cycle has numerous tools to help do so. And it goes without saying that such knowledge could only improve managerial performance.

Master Cyclist Principles

For the past three years, my “master cyclist” project at the University of California, Irvine, has evaluated companies’ market literacy, forecasting capabilities and elements of macroeconomic strategy, using quarterly and annual earnings reports, Internet and Lexis-Nexis searches and interviews with key executives. Out of this research a set of managerial principles has developed, defining how a market literate management team would approach short-run functional decisions regarding inventory, production, marketing and pricing as well as more strategic choices regarding capital expansion, acquisitions and divestitures.

Inventory Control and Management.

An executive team that believes there may be a recession on the horizon would begin to cut production to avoid the cost of being caught with large amounts of inventory. Conversely, in anticipation of recovery, the team would increase production so as not to be caught with too little inventory as the economy picks up.

Supply Chain Management.

Large stockpiles of production inputs can weigh down the bottom line as the business cycle slides from late expansion into early recession. Such stockpiles are all the more costly because a company will likely have paid premium input prices at the late expansionary stage of the business cycle under conditions of robust demand. One obvious broad-tuning solution would be for an executive team to trim input purchases in anticipation of a recession just as the company is cutting back on production. More subtly, the team would recognize that within the broader economic cycle, there are individual cycles that can affect different sectors of the economy.

Human Resource Management.

Just as a market literate executive team would try to avoid being caught with an inventory overhang, it would also begin to trim the work force in anticipation of a contraction — even as rivals continue to hire at premium wages. Perhaps more subtly, the team would also begin to hire sooner than competitors in anticipation of an upturn. In this way, a company may be able to cherry pick from the relatively larger pool of unemployed labor.

Marketing and Targeting.

As a countercyclical measure, an executive team would want to temporarily boost marketing expenditures to trim inventories in anticipation of a downturn. Once inventories were thinned, marketing expenditures would be ratcheted down to weather the contractionary storm. More generally, the executive team would proactively change the messages of the marketing effort to reflect the changing mood of the economy.

Pricing.

If a company is able to exercise pricing power in its industry, its executive team would want to take the lead in raising prices as an expansion takes hold and lowering prices as the economy softens. In this way, the company builds revenue in good times and protects market share in bad times.

Capital Expansion and Modernization.

An aggressive capital expansion program creates the need for a large cash flow to service the additional debt. However, with the onset of recession, revenues can fall dramatically, leaving companies in a cash-flow and credit crunch. To avoid this, an executive team would trim its expansion plans well in advance of an anticipated recession. More subtly, the team would also seek to initiate capital expansion plans in the perceived trough of the business cycle so as to have new production, operating or retailing facilities ready for when an anticipated recovery arrives. In such a trough, short-term interest rates have typically been lowered by a stimulus-seeking Federal Reserve, while longer-term interest rates have usually fallen because of the recession, creating favorable credit conditions that include lower capital costs and longer lead times. Under such conditions, an executive team might also choose to replace and renovate equipment and retrain workers — when costs are low and the opportunity cost of lost capacity utilization is minimized.

Acquisitions and Divestitures.

While broad strategic considerations inform the decisions to acquire or divest, business cycle considerations can provide important guidance as to when to implement the decision. Ideally, an executive team would pursue a countercyclical strategy, acquiring companies at bargain prices during downturns and divesting unwanted companies at premium prices in the late stages of expansion.

Managing the Business Cycle in Practice

The master cyclist principles are very intuitive and, by themselves, quite uncontroversial. However, devotees of the random walk view would argue that they are also moot since they believe that movements and turning points in the business cycle cannot actually be anticipated. Nevertheless, there is a good deal of evidence that the signs are there to be seen, and there are numerous examples of companies that explicitly manage with a market literate approach designed to spot them.

For example, leading up to the 2001 recession, which officially began in March of that year, a business cycle-sensitive management team would have noted that the yield curve progressed from a fairly normal shape in June of 1999 to a progressive flattening of the curve in November of 1999. More alarmingly, the yield curve then moved to its “humpbacked” inversion between the 2-year and 30-year Treasury securities in March of 2000 — a recessionary signal coming exactly four quarters before what would be the official start of the recession.

The market literate management team would also have noted in the period that the S&P 500 index was falling precipitously from its March 2000 high leading up to the March 2001 recession: almost 15% by October of 2000 and more than 25% by March of 2001.

As for the Index of Leading Indicators, by July of 2000, it had already turned down for three consecutive months. Historically, this suggests an almost 60% probability of recession within four quarters. By September of 2000, this index had turned down for five consecutive months, raising the probability of a recession (based on historical experience) to roughly 75% within three quarters.

On the basis of just these indicators, it seems reasonable to conclude that there were strong and very discernible warning signs of a possible recession. At least some companies seemingly took these warning signs into strategic consideration. As CEO Ralph Johnson’s statement indicated, cycle-savvy Johnson & Johnson cut its capital expenditures by over $100 million — the first decrease in seven years. As the company significantly built up its cash reserves, it saw double-digit growth in both revenues and earnings. These positive indicators, coupled with a rotation by investors into defensive sectors like health and medical care stocks as the bear market took hold, helped give J&J’s stock a double-digit boost in both 2000 and 2001.

Southwest Airlines Co. offers an equally interesting example of a market literate company that relies heavily on macroeconomic forecasting to manage all phases of its business. The company’s own highly sophisticated model has been particularly useful in its fuel-cost hedging strategies. While almost all airline companies engage in hedging, most typically hedge less than half of their fuel needs. Departing from this industry practice in early 2000, Southwest opted for a close to 100% fuel hedge for the third and fourth quarters on the basis of an internal forecast of a significant shortage of crude oil. As oil prices soared above $30 per barrel, Southwest saved over $110 million in fuel costs and saw its earnings increase for the year by more than 30% — almost three times the industry average.

Like Southwest, chemical giant and highly business-cycle-sensitive DuPont has invested heavily in its own forecasting capabilities. DuPont employs a team of economists, its internal forecasting model has been a long-time component of the aforementioned Blue Chip Survey Consensus Forecast, and its forecasts have been recognized for their accuracy by The Wall Street Journal, among others.

As 1999 ended with record profits for DuPont and the economy entered 2000, DuPont senior economist Robert Fry began to voice concerns about the effect that soaring raw materials costs, rising interest rates, higher oil prices and weaker housing starts might have on the by-then eight-year-old expansion. By early to mid-2001, Chairman and CEO Chad Holliday had not only warned shareholders of significant “downward pressure on earnings,” but he had also assured shareholders that DuPont was “taking the right steps to manage through a global economic slowdown.”

Like J&J, DuPont cut capital expenditures but did so even more dramatically, lopping off $400 million or 20% of the annual CapEx budget in 2001. More subtly, DuPont used the deepening recession to quickly accelerate the pace both of its modernization programs and of the shutdown of a number of aging facilities — all with an eye to changing the company’s product mix in response to changing global economic conditions.

On the human resources front, DuPont moved equally dramatically — albeit painfully. In early 2001, the company announced it would cut 4,000 jobs, or about 4%, while also cutting contract personnel by another 1,300. Together, these actions helped DuPont maintain profitability throughout the downturn.

Similarly, energy provider Duke Power, based in Charlotte, North Carolina, attempted to align its acquisition and divestiture strategies with business cycle movements. In 1999, as the stock market boomed, energy prices continued to rise and the energy sector prospered, Duke completed its sale of Panhandle Eastern Pipeline and Trunk-line Gas Co. to CMS Energy Corp. at a premium price in a deal valued at $2.2 billion. Just four years later, cash-strapped CMS would be forced to sell off this property at a $600 million loss. Meanwhile, in late 2001, with stock prices and valuations heading significantly downward in the energy sector, Duke flipped its strategy to acquire Westcoast Energy Inc. at a price that was immediately accretive to earnings. “We sold plants at the top when prices were at their peak,” CEO Richard Priory noted. “Now that everybody’s selling, we’re anxious to buy.”

In contrast to these companies, Internet router market leader Cisco Systems Inc. provides an almost textbook case of a management team that rejected the use of macroeconomic forecasting to manage its production, inventory and supply chain functions — and paid a heavy price. By design, the company’s internal growth models lacked the many macroeconomic variables commonly used in traditional forecasting models. This approach was rooted in the belief, as one top executive put it, that “the economy is too complex to get anything meaningful out of such broad numbers as GDP or interest rates.” As the 2001 recession hit, Cisco’s internal forecasting model had become increasingly reliant for its inventory and production decisions on orders from (but not sales to) its suppliers and customers. Unfortunately, this system was riddled with perverse incentives: Cisco’s resellers inflated their demand forecasts to protect against inventory shortages. These overinflated forecasts rippled through the supply chain, while Cisco’s problems were further compounded by its reliance on forecasts from new startups lacking historical experience in the marketplace. As CEO John Chambers’ statement implies, Cisco was caught with a huge amount of product and supply chain inventories. Eventually, it wrote off over $2 billion in such inventories, even as it laid off more than 8,000 employees.

Toward More Market Literate Management

From the random walk perspective, it can certainly be argued that the successful companies in the above examples just happened to find themselves on the right side of the business cycle, while Cisco was simply unlucky. That hypothesis certainly can’t be rejected statistically. However, it is also true that the successful companies identified above clearly demonstrated a belief in business cycle literacy. From this perspective, it seems implausible to suggest that the strategic, tactical and functional decisions of such companies are not, at the very least, somewhat better informed by intelligent speculations about the business cycle.

More broadly, while the predictability of the business cycle remains very much a debate among both academics and managers, it seems quite beyond debate that the line between corporate success and failure is often defined by the decisions that are made around key turning points and movements in that cycle. It follows that — in MBA classrooms and corporate boardrooms alike — as economic forecasting indicators and techniques continue to evolve and improve, so too should our understanding of the business cycle and the articulation of the various principles associated with effectively managing it.

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