This chapter is from the book
This chapter is from the book
This chapter is from the book
Inconvenient Truths
Part of the reason why the failure rate is so high is because there are three inconvenient truths about change:
- Change is hard.
- Change is expensive.
- Change takes time.
Change Is Hard
First, although we would like change to be easy, the inconvenient truth is that it is hard. Changing behaviors, especially patterned behaviors, is hard precisely because of how behavior patterns come into being. The process is as simple as it is powerful. To illustrate the process, let’s take a simple behavior—getting out of bed at 5:30 a.m. and exercising. The first time you do this, you do it in anticipation of the positive consequences outweighing the negative ones. If you get out of bed and exercise and the anticipated positive consequences turn out as expected, you are likely to repeat the behavior. If, as you repeat the behavior, you get a pattern of reinforcing consequences, the behavior pattern deepens. If you don’t get reinforcing consequences, you won’t develop the pattern of getting out of bed at 5:30 to exercise. It is that simple.
However, at a deeper level, it is not quite this simple. The complexity comes from the fact that positive and negative consequences are not so cut and dry. Whether a consequence is positive or negative and how strongly it is one or the other can be influenced or even determined by perception. For example, it might be an objective fact that as a consequence of exercising, a person’s cholesterol declined by 21.3 percent. However, how important or positive that outcome is, is not absolute; it is a function of a subjective valuation imposed by the individual. One person might view this as a great benefit and another might view it as a relatively minor benefit.
In other cases, whether a consequence is positive or negative might be entirely dependent on perception. For example, getting up at 5:30 a.m. might objectively mean that you have to go to bed at 10:30 p.m. instead of 11:30 p.m. in order to get seven hours of sleep. One person might view going to bed earlier as positive, another as neutral, and a third as negative. Again, even if two people viewed going to be earlier as negative, one might view it as highly negative and another as only moderately so.
Despite all of this, you can be sure that if one person is getting out of bed at 5:30 to exercise, it is because the net consequences (objective and subjective) reinforce this behavior, and if another person is staying in bed at 5:30 and not exercising, it is because the net consequences (objective and subjective) reinforce this behavior.
However, even when past reinforcements stop working, we don’t immediately change our behavior. This is in part because humans are biologically hardwired to resist change. Yes, that’s right. We are programmed not to change. Whereas plants may evolve and survive through random variation and natural selection, humans prefer not to. We are naturally averse to random variation (that is, random behavior) and therefore random deselection and elimination. We are wired to survive, so we hang on to what has worked in the past. We hang on to successful past “mental maps” and use them to guide current and future behavior.
Our tendency to hang on to old mental maps, especially if they have worked, is easy to illustrate with an experience I had with two colleagues a few years ago in Japan. We were there attending an international conference, and for my two colleagues it was their first time in Japan. Because I had previously lived in Japan, they asked me to take them to a very traditional Japanese restaurant. I agreed. After selecting the restaurant, I gave them some cultural tips. I told them that the restaurant would be down a back alley and not on a main street. I informed them that when we arrived, we would need to slide open a door on wood runners, and the runners were not recessed. Therefore, they would have to carefully step over the runners so as not to trip. Once past the door, we would enter a receiving area where we would take off our shoes and then step up into the restaurant proper and put on some slippers before being escorted to our table.
That evening we arrived at the restaurant and I slid open the door and stepped in. My other colleague, Allen Morrison, then stepped over the wood runners and entered the receiving area. The next thing I knew, there was a thunderous crash behind me. I turned back to see my colleague, Hal Gregersen, staggering in the doorway with blood dripping down his forehead. To understand what happened, I should tell you that I am 5′10″ and Allen Morrison is 5′9″. Hal is 6′6″. While he was looking down to step over the wood runners, he smacked his head on the top of the door jamb. As funny as this story is, two nights later, we went to the restaurant again and I stepped in, Allen stepped in, and—crash!—Hal had a matching cut on the other side of his forehead. A few days later on the last evening of the conference, we went to a different but similar restaurant. I stepped through, Allen stepped through, and Hal...ducked. Some might say the story illustrates that Hal was a slow learner, but it is more than that. Hal’s mental map for entering restaurants up to that point in his life did not require him to duck when entering. Not ducking had worked for him for more than 38 years. As a consequence, it took a smack in the head—actually two smacks—before he changed his mental map.
So change is hard, and the more successful what we need to change has been in the past, the more difficult changing it is. We might not wish it to be so, but inconveniently it is.
Change Is Expensive
The second inconvenient truth is that change is expensive. Although we might wish it were cheap, it typically requires significant time, money, effort, blood, sweat, or tears.
Often this is because in order to get new outcomes, you have to first invest time, money, and so on into generating new inputs. For example, in the early 1990s, IBM needed to change from selling products to selling solutions. Selling solutions had the potential of generating both significantly more revenue in general and much more profitable revenue in particular. As a consequence, selling solutions had great appeal. However, producing new sales and profits from solutions required a number of new inputs and capabilities for sales people.
Let me offer just one example to illustrate this. Previously, selling products such as desktop computers and servers required IBM sales people to contact IT purchasing directors. These folks, like the IBM sales people, were highly knowledgeable in the technical specifications and performance of the specific products. In comparing IBM products with those of competitors, both these IT purchasing directors and the IBM sales people spoke the common language of “geekenese,” or its derivative, “techenese.”
Unfortunately, unlike products, solutions were not sold to IT purchasing directors but to CIOs and CEOs. Even more unfortunately still, these business folks did not speak “geekenese”; they spoke business. As a consequence, quite literally, the IBM sales people had to learn a whole new language, and to some extent forget a well learned and loved language. Without learning this new language, they had no hope of selling solutions. As anyone who has learned and become fluent in a new language knows, it takes significant time, money, blood, sweat, and sometimes tears to get to the point of proficiency, let alone mastery. In that light, one should not be surprised that it took literally millions of dollars to train IBM sales people to speak the new language of CEOs in order to sell solutions to them.
The second reason that change is expensive is that even when you provide people with new inputs, you often have to spend money and effort to change their perceptions of outcomes. For example, in the case of IBM, I spoke to many sales people who even after having learned the language of business were afraid to speak to CEOs and other senior nontechnical leaders. Why? They were afraid that these executives would ask them questions about business that they could not answer. Even though these IBMers were now fluent in the language of business, they knew that they were not experts at business. As a consequence, it was easy for them to imagine that CEOs and other executives could ask them questions about business that they simply could not answer. Thus, even though they now had command of the language of business, they were not yet inclined to use it.
In pushing this analysis further, I asked the sales people why they thought business executives might ask them business questions to which they might not have answers. Their answer to my query proved very instructive. Put simply, the answers came out along the following lines: “Well, when we used to sell products to IT purchasing directors, they would ask us all sorts of questions about what we were selling, and we needed to be able to answer any and all of their questions. Not being able to do so was a sign of incompetence.” They took this past frame and superimposed it on the new conversations. They assumed that as they had been expected to answer any and all questions about products they were selling, they should also be able to answer any and all questions about solutions to business problems.
Clearly, as long as they viewed the conversations with CEOs about solutions within the same framework as their past conversations with IT purchasing directors about products, the encounters were indeed fraught with risk and were best avoided—no matter how fluent one was at speaking the language of business. However, the key to selling solutions was not in answering any and all possible questions about a solution, but in asking the right questions to discover what sort of solution was needed. As you might imagine, changing this perception was not free. I literally had to role-play and visually demonstrate how the encounter with CEOs should go. It was only after the sales people I was working with changed their perception of the conversation that they changed their view of the likely consequences. And only after changing their perceptions of the likely consequences were they willing to put their new “language” capability to use.
For leaders of change, this gets to the heart of what makes change expensive—because people act on their perceptions and because you cannot control how people perceive things, changing perceptions is never cheap. Machiavelli captured this notion quite well more than 500 years ago:
- There is nothing more difficult to carry out, nor more doubtful of success, nor more dangerous to handle than to initiate a new order of things. For the reformer has enemies in all those who profit by the old order, and only lukewarm defenders by all those who could profit by the new order. This lukewarmness arises from the incredulity of mankind who do not truly believe in anything new until they have had actual experience with it.
So change is expensive because changing outcomes, changing drivers of outcomes, and changing perceptions of outcomes all come at a price.
Change Takes Time
The third inconvenient truth is that although we might wish for change to be over in a flash, it often takes a significant amount of time for a change to take hold. There is a very simple reason for this. By definition, change requires doing something new. Common sense tells us that you don’t go from not having done something at all to doing it well in an instant. This is why we talk about “proficiency curves,” as illustrated in Figure 1.1.
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Figure 1.1 Proficiency curve.
Whether the change is from selling products to selling solutions, or from not playing the violin to playing it, proficiency comes over time and typically follows an “S-curve” of improvement. The more complex and difficult the new behavior, the longer it takes to become proficient at the new thing.
As I said, intuitively we understand this. To illustrate it, let me return to the IBM example. Would you be surprised to learn that gaining the requisite proficiency in selling solutions takes an individual 2–3 years? Hopefully, based on just the things I’ve covered so far in this chapter, you can imagine why this is the case. For example, as I already mentioned, IBMers had to learn the language of business and to some extent had to unlearn “geekenese.” IBMers had to switch from answering narrow, technical questions to asking broad, probing questions. They had to switch from working solo as a technical expert to leading a diverse, cross-functional team. Getting up the proficiency curve on all these and other dimensions cost time, money, blood, sweat, and tears.