Most business are pro-cyclical, meaning that their success and viability is positively correlated to the strength of the economy. Ordinarily, the fundamental aspects (i.e. company-specific revenue and income management) of running a business are of paramount importance, with forecasting and adaptation to changes in the economy a secondary consideration. However, in the current economic downturn, it may well be that accurate economic forecasting deserves much greater attention, and behooves one to shape overall business management according to these changing economic dynamics.
For purposes of this discussion, “business analysis” is the analysis and scrutiny of business results in hopes of identifying ways of improving them. During “ordinary” times, business analysis is often neglected or done in an ineffective manner. One way of identifying whether business analysis is being properly performed is to gauge its results – if it seems to be of no or little value (i.e. not illuminating ways to improve sales and revenues) then it is most likely being performed incorrectly.
Business analysis is especially critical during this economic downturn. Many facets of the economy and capital markets are experiencing very rapid and historic changes that only a year or two ago were virtually unimaginable. This change is impacting many businesses in a most adverse fashion. Companies across the business spectrum have started to adapt to these adverse economic conditions in a number of ways, including such standard actions such as job cuts and price cuts. But are these, and other actions such as tighter “cash management”, which have become accepted “standard operating procedures” during challenging times, appropriate and adequate for the new and unique business and economic environment?
Business analysis is in many ways the answer to this question. “Knee-jerk” and obvious “common sense” “solutions” to garden-variety economic weakness may be inappropriate and/or inadequate actions during this period of economic malaise. Furthermore, with the credit and lending markets very restrictive, lenders and investors will seek to minimize their risk. One way of doing this is to demand evidence that a company has enacted an effective, controlled approach to managing the business. Furthermore, during these difficult times, to the extent that a company is able to adapt properly, it could attain significant competitive advantage.
Although business analysis may now be of heightened importance, it will be even harder to properly perform. In addition to the difficulty of assessing and adapting to the fundamental drivers of success, the unpredictable and heretofore historic changes in the dynamics of the economy may well present a factor that could render traditional business analysis at best invalid. In order to accurately navigate, businesses may have to perform business analysis at a level that is considered “beyond sophisticated.”
During periods of economic distress, it is common for companies to believe that “greener pastures” await at the lower end of the price spectrum. This belief has its roots in many origins, some legitimate (but possibly misapplied) as well as illegitimate. It is often incorrect business analysis that leads a company to believe that its current “market space” holds “low” or “no” potential for further improvement.
The belief that the lower price point holds greater opportunity, and therefore should be pursued, holds many potential dangers and caveats. Perhaps chief among them is that many companies are concurrently coming to the same conclusion; yet history has shown that becoming successful at the lower price point demands a certain set of skills and disciplines that are often elusive. Being, or becoming, a successful low-cost producer is often difficult. Even if it is possible to attain this status, it will take considerably more time, money and skill than many companies currently possess.
While the scope of what needs to be vigorously analyzed varies among companies, there are a few common areas that most likely deserve scrutiny, as listed below:
- Cost structure – On a basic level, are the costs fixed v. variable? Having a very good idea of this dynamic, and how it relates to the changing economic landscape, is key.
- Forecasting – Ordinarily, forecasting encompasses what is expected or what can be reasonably expected. However, during this time of massive economic uncertainty, it could prove valuable to consider “unreasonable” scenarios. For instance, during “normal” times a company would typically not consider a scenario under which revenue would fall 10% or more on a yearly basis. However, in today’s environment, this may now be in the realm of possibility. During the telecom “crash” earlier this decade, it was not uncommon for telecommunication equipment manufacturers’ revenues to decline at double-digit rates, and the resultant damage was severe. While this type of waterfall decline in revenues may or may not happen on a general scale now, it is probably worth considering. Most businesses are not flexible enough to successfully adapt to revenue drops of this magnitude, especially in a short period of time. By being aware of the possibility of this type of drop, and its effects on the business, companies can at least begin to theorize what may need to be done to maximize their viability and health.
- Cost-cutting – Rapid, severe cost cutting is often instituted during difficult economic times. Due to the rapidity and severe nature of this decline, it is to be expected that cost-cutting will be very prevalent. One of the questions that may arise is whether the sudden need for severe cost-cutting is in itself a sign of a deficiency in one or more areas, including forecasting, financial management, or strategy? While it is impossible to generalize, this topic deserves scrutiny and separate discussion.
- Pricing – As previously mentioned, price-cutting and other price-related actions are often used rather indiscriminately during times of economic distress. Furthermore, the belief that “greener pastures await” at a lower price point often drives strategic actions that can be detrimental. These types of pricing and revenue management subjects are critical.
- Dealing with immense uncertainty – It may be that, all things considered, the regular methods of forecasting and projecting results become invalid. This happens because the uncertainty and “randomness” of occurrences is so different from the historical norm that prediction with a sufficient degree of certainty becomes very difficult to attain. Revenues and profitability can no longer be accurately predicted. When this occurs, a company can either stop projecting/forecasting, because it is ineffective; or continue to project/forecast in an ineffective manner. Obviously, neither of these options is palatable, especially at a time when accurate forecasting and projecting results is of paramount importance. There might be another way to surmount this obstacle. Instead of, or in addition to, attempting to project results, one may choose to “turn around” the equation. This might be done in a number of ways for a variety of purposes. A simplified example might be to formulate an expression that would allow an executive to say, “In order for us to attain a 2% net margin, we will have to have 5% revenue growth.” While this type of projection is not as valuable as predicting results in an accurate fashion, it nonetheless “frames” possible results in a way that allows an understanding of the business dynamics, as well as a way in which to gauge the likelihood of a scenario.
Never has there been a time when performing business analysis has been more valuable. If done correctly, it can allow a company to possibly thrive throughout this downturn, or at least “weather the storm.” Conversely, those businesses that don’t engage in meaningful analysis might find themselves in a situation far less desirable. Even if the less fortunate companies survive, it is often at a far smaller size. While it is easy to think that this type of company will rebound to its former size when an economic rebound occurs, this type of assumption has not always proved correct.
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