While almost all HBS alumni think very highly of themselves, they are also the first to admit that life is full of constraints and conflicts. It can be a meeting that goes on and on while the family is waiting for a major celebration. It can be a critical strategy decision that has to be made quickly without enough data. It can be such a flood of data that it’s hard to see where to start. It can be a conflict between the current rush assignment and the new grand idea that just occurred to the boss (or, worse, the boss’s boss) today.
Resource constraints and conflicts are inevitable. These constraints are wellillustrated by the case study method. The tremendous amount of case workload, the time conflicts between work and private life, the lack of perfect data despite the significant amount of background given in each case study, all reinforce the reality that people are always constrained in some way. The keys to managing resource constraints and conflicts include discipline, courage, and tools.
Discipline means that instead of immediately committing to and attempting to do everything, one remembers to take a step back to question if the resources can adequately meet the demand. If not, one must have the courage to discuss the constraint with the others involved and use the appropriate tools to prioritize and manage the compromise.
Courage means to be able to highlight the possible constraint and work out a solution with the other people involved. These other people could be your spouse, children, boss, clients, or colleagues. This is especially important in managing upward. Often, especially early on in their careers, people are so anxious to prove themselves that they do not have the courage to bring up the issue of resource constraints. It is always better to have the courage to discuss the constraint up front and early rather than to fail to deliver what is promised.
Some of the key tools for prioritizing and managing constraints:
There are two categories of big pictures:
This is a true story: When I was a new consultant, my boss asked me to get some data for him in a week’s time. Eager to please, I told him I could give it to him in half that time. Unfortunately, it took longer than I thought. After three days, I told him it would take me another two days. But I was confident I could finish before the original deadline he’d given me. I was expecting that he would be OK with that since I would still be ahead of what he originally asked for. But he was furious. Because I had told him to expect the data in three days, he had planned on getting the data early. His plans would need to be totally revamped because of my delays. He was upset and so was I.
From then on, I never forgot the importance of setting the appropriate expectations. Two rules I now abide by at all times:
There is a rule of thumb that has worked time and again for me. This is the 80/ 20 rule, which says 80 percent of the total output is or can be generated by roughly 20 percent of the total input. For example, the following observations are probably true:
The 80/20 rule was first developed by Vilfredo Pareto (1848–1923), a French-Italian sociologist, economist, and philosopher. While researching economic conditions in his native Italy, Pareto determined that 20 percent of the population owned 80 percent of the land. Subsequently, while working in his garden, he discovered that about 80 percent of his peas came from just 20 percent of his plants. Based on these and other observations, he determined that for any series of elements under study, a small fraction of the number of elements usually accounts for a large fraction of the effect. Over time, Pareto’s observation became generalized as the 80/20 rule.1
Naturally, 80 and 20 are not rigid numbers. These are estimates that mean that the bulk (usually over 60 percent) of results can be attributed to a small fraction (usually less than 40 percent) of the input.
The 80/20 rule is extremely helpful for prioritization. It means that the top 20 percent should be given the most attention–it can be the top 20 percent of the customers, 20 percent of the data for analysis, 20 percent of the staff who are getting the highest pay.
An example from my early consulting experience solidified my belief in this rule: I was working for a relatively unsophisticated client in China. I found that its sales department evenly distributed sales staff time among the customers, so each customer got the same amount of time and service from the sales staff. As a result, each salesperson was assigned 10 customers and instructed to serve all of them equally well. While the company overall was profitable, revenues and profitability were not growing. When we interviewed the major customers, we found that they felt my client’s sales staff was “all right” but not “stellar” in their service. They did not feel my client valued them. Therefore, even though they continued to buy from the client, they were also giving business to other companies that were giving them “similar or better service.” When we interviewed the small customers, they were very impressed by my client valuing them as if they were a big customer. However, although they wanted to buy more, their size did not allow them to increase their orders by much.
In addition to ineffective customer service, such allocation of resources is also inefficient from a customer profitability perspective, as shown in Figure 5.1.
In the end, the study recommended a reallocation of resources—80 percent of the sales force time should be spent on the 20 percent of major or growing customers.
Another example of the 80/20 rule came up in my recent study on a property investment company, as shown in Figure 5.2.
Figure 5.1 Return on Sales Effort
Sometimes quick results are better than big results. This can be due to a variety of reasons: the need to build credibility for yourself, your team, or your project; a business crisis such as the need for immediate cash; morale; or too much time and effort needed to get big results. In such cases, instead of applying the 80/20 rule, which focuses on the biggest impact, it may be more effective to focus on capturing the “low-hanging fruit.” As the term implies, it means exploiting the opportunities that are easiest to capture. For example, I was once involved as the consultant for reengineering a state-owned petrochemical company in one of the Asian countries. The company was experiencing explosive growth and found that it could not hire enough qualified people to support that growth. The goal of the project was to redesign key processes and functions to make better use of the available human resources. The company had about 20 offices and refineries across the country. When planning the project, we had a few options. Here is a simplified summary of the options we considered:
Figure 5.2 Rental Returns
| Options | Key Considerations |
| 1. Start with the largest offices and refineries | 80/20 rule |
| 2. Start all at the same time | To shorten the total duration of project Find “low-hanging fruit” that can help build credibility for project |
| 3. Start with a small refinery that has outdated processes and a significant manpower shortage and then roll out to rest of company |
In the end, we chose approach 3. This is because some senior client executives were skeptical of the project and the involvement of expensive external consultants. By quickly achieving results in a small refinery, we built credibility that made it feasible to get support for a rollout to the rest of the company. We were also able to gather some best practices that were useful as we rolled the project out.
It is obvious that many factors are beyond our control, both in our personal lives and in business. Plan B means to have a backup plan, to have a plan for the worst-case scenario, to have a plan to turn to when your assumptions turn out to be wrong. It can be completely different from the original plan or it can be a moderation, change, or adaptation of the original plan should that plan become infeasible. While this seems logical and natural, the reality is that Plan B is often either forgotten or not done properly. This can be because of negligence, wishful thinking that Plan A will work just as planned, or lack of resources.
It is true that Plan B, when developed, is very often not used. But Plan B is like car insurance. Many people have the insurance but never claim enough to cover the premium paid. This is how insurance companies can make money. However, you do want the insurance just in case you get into an accident. The chance of a major accident may be slim. But you want insurance just in case it happens. This is the rationale behind insisting on having a Plan B.
I keep a story and an adage in mind to remind me of Plan B. The story (which is true): There’s a U.S. television reality show called The Apprentice, hosted by the high-profile real estate tycoon Donald Trump. Each season, a group of contestants including business school graduates, entrepreneurs, lawyers, and so on have to solve many business challenges under a tight time frame. Contestants are eliminated until the final two. Then there is a final challenge and a winner is selected from the two. The winner will get an apprenticeship from Trump.
In the season finale, the two finalists were asked to each plan a big charity fundraising activity. One finalist was an HBS graduate with a doctorate from another leading school, who had been outstanding throughout the competition. He was definitely the front-runner going into the finals. He was asked to plan an outdoor charity event within a very limited time. While he was planning, somebody informed him that the weather forecast indicated possible rain on the day of the event. However, working under tremendous time pressure, he ignored the information. The day came and rain was pouring down. He had no Plan B. He had to scramble to change everything in his Plan A. Needless to say, he paid a high price for the mistake.
In addition to this story, I find Murphy’s Law (an oft-quoted Western adage) useful as a reminder of the need of a Plan B. Murphy’s Law has many versions, but the one I go by whenever I plan is “What can go wrong will go wrong,” especially when you least expect and can least afford it. Of course, I don’t mean you have to have a Plan B for everything that “can go wrong.” That would be too arduous and too costly. The factors to consider in determining whether a Plan B should be done and how much effort should be put into it can be expressed in a qualitative formula:
With a “qualitative formula,” hard data and numbers are not necessary. It is just an aid to a qualitative decision. The formula is self-explanatory:
The final decision on the need for Plan B is a judgment based on putting all three factors together.
I learned one thing early on in my career: if in doubt, ask. For many different reasons, including overconfidence, lack of confidence to ask, or simply lack of time, many people have a tendency to make unfounded assumptions. Whenever I make assumptions, I always remind myself of some words of wisdom I learned from my superiors very early on in my consulting career: “Do you know what happens when you assume? You make an Ass-(out of)-u-(and)-me.” Needless to say, these words of wisdom came after I made some poor assumptions in some consulting projects. You can imagine the damage to your credibility if you are questioned on your assumptions and you cannot defend them, as in this exchange:
CLIENT (OR YOUR SUPERIOR): I see in your strategy study you assume inflation of 5 percent a year in the next few years. What makes you say that?
YOU: That’s the historical inflation rate.
CLIENT: Why did you assume it will be the same in the next few years?
YOU: (silence because any answer will look bad: I had no time, I was sloppy and did not think hard . . . )
Therefore, it is important to remember that any assumption can be questioned. So, whenever you make an assumption, you must ask yourself— can I defend this assumption? Possible defense includes a credible source (such as government or expert published research data, or interviews with experts or the client’s senior management) or a clear logic (such as the historical rate is studied over 50 years and is a good medium-term average, or sensitivity analysis indicates that inflation has very little impact on our decisions and hence we did not spend too much time on it). If you have a source or logic, others may still disagree. But their disagreement will lead into a discussion designed to refine the assumption, and you will not lose credibility as a result of making it.
Note
1. Ethan M. Raisial and Paul N. Friga, The McKinsey Mind (New York: McGraw-Hill, 2002).