Part 9 (1/2)

PIE FIGHT.

There's a problem with pie charts: They're in the middle of a war.

Among information designers, there is a long- running battle raging about the effectiveness of pie charts for conveying data. On the one hand are people who think pie charts are fine-easy to create (with the right software), visually pleasing, and easy to read. On the other front are people who believe that since our eyes are less well adapted to accurately measuring proportional size differences in slices than they are in straight verticals and horizontals (which is true), we shouldn't ever use pie charts.

In fact, there is a time and a place for both, and the proof is in the pizza. If you've ever been to a kindergartner's birthday party, you'll have seen that six- year- olds have no problem picking the biggest piece of the pie. If they can figure it out, so can we. So if you prefer round pizza, feel free to use a pie chart. If you prefer your pizza square, there is an equivalent chart to fall back on: the stacked percentage chart. It shows the same information, just lays it out in straight lines.

If the differences among slices are so critical yet so small as to be difficult to visually detect, you're better off going back to a nonpictorial table anyway.

The stacked pizza, or vertical percentage chart.

But that's one of the challenges with the typical how much chart. Because it shows only quant.i.ty, it's easy to forget other critical differences that might exist between the items being measured. In other words, although the numbers we see in a quant.i.tative comparison may be accurate, they can still mislead us. For example, if the pie chart on page 160 were the only measure I had of customer quant.i.ty, I'd in theory have no choice but to a.s.sume that I should allocate 75 percent of my marketing budget to my accountant customers, since they represent 75 percent of registered users. But that might not at all reflect sales reality.

By total spend, accountants are our biggest customer group.

As we continue to look through our sales numbers, let's say that we come across the actual client purchase orders (POs). These POs show the final amounts paid and by whom-not who registered the software, but who bought it. Using another bar chart (since we're looking at absolute numbers, not percentages), we see that accountant customers spent $100,000 with us last year, while salespeople spent only $5,000.

Here we see a different story emerge. While accountants represented three-quarters of our total registered customers, they bought only slightly more software than did the technicians, who were the second smallest customer group in size! That's interesting. Who'd have thought that the technical people were the ones doing so much buying?

To understand how this is true, we're going to have to look at one more chart. This time, let's factor in the quant.i.ty of each customer type against how much money each spent. Doing the math (total spend divided by number of customers per type) tells us the following: When we factor in the number of customers against their spending, we see that the average exec spends $5,500 on our software, the average tech $5,300, but the average accountant spends only $640.

Whoa! Look at that. While execs and technicians account for just half of all purchases, individually each has nearly nine times the individual spending power of the accountants. Nothing we'd looked at in any data before would have led us to see that. Although this chart doesn't tell us why the numbers shake out like this, it certainly gives us a lot to think about. Perhaps the technicians are doing much of the buying on behalf of the accountants. If so, those technicians have tremendous spending power. And just four execs are buying even more? That tells us something new about purchase decision making at our client: It falls disproportionately on the two most disparate groups. It also tells us that we'd better start looking carefully at the buying process of the technicians and execs.

All this should be giving us an inkling of where our sales problem may originate-and that's what we'll be looking at next: the where framework. But before we go there, let's review. The pictures shown here-numeric comparisons, pie charts, and bar charts-are just a few of the variety of ways to show how much or how many. As we saw with portraits, different businesses and different problems will demand different types of charts to represent quant.i.ty; but also like portraits, they are all just variations on the same theme. All are ways to show us how many or how much there are of the whos and whats we represented with our first framework.

By individual spending, execs and technicians are our biggest customers.

* If you're interested in a detailed explanation of when to use each of the myriad types of charts available, there are lots of great books out there. See Appendix C: Resources for Visual Thinkers for recommendations.

CHAPTER 11.

WHERE IS OUR BUSINESS?.

PICTURES THAT SOLVE A WHERE PROBLEM.

Moving Out Across the Map The numbers we looked at in the previous chapter show that the executives and technicians at our client are doing a disproportionate amount of the buying. That was interesting and unexpected: We'd always a.s.sumed it was the accountants who bought most of our software since they were the ones who used it. This twist has got us wondering if we really understand the hierarchy of our client's business; it appears that the technicians are in a position of greater influence than we knew.

So now we've got a where problem-not a geographic ”where” as in who is located in what building or which city-but rather a structural problem. We want to see where the now-critical technicians fit into the decision tree of our client's organization relative to its accountants, salespeople, and execs. What we need is a map of our client's business structure. And even though it's not really a geographic map, we go about creating it as if it were.

REVIEW: A MAP SHOWS WHERE.

Maps can be Venn diagrams, schematics, landscapes, ”think maps”: No matter how different they may look, they're all drawn the same way and all show the same thing-the spatial relations.h.i.+p of one object to another.

After how much, we saw where objects were in relation to one another. We noted their positions, relative orientations, and distances apart. In order to show these locations to someone else, we use maps to represent placement, proximity, overlap, distance, and direction-and that doesn't apply just to geography: Maps make all kinds of ideas about the spatial relations.h.i.+ps of objects unexpectedly clear.

Because of their versatility, maps are the most flexible of all six frameworks, which means that various kinds of maps may not look all that much alike. The fact is that they really are, especially in the way we go about making them and the spatial relations.h.i.+ps they ill.u.s.trate. If we start by drawing in the most prominent feature of our ”landscape”-whether that is a mountain, a person, or an idea-and have a clear set of coordinates defined, it's a relatively straightforward matter to move outward and add more and more features and details, mapping overlays of complementary data on top to indicate everything from borders and distances to connections and sets of shared traits.

Maps are the most familiar visual thinking framework we have: from organizational charts (which everybody knows how to draw) to Venn diagrams (which everybody understands) to good old treasure maps (which everybody loves to look at), maps are our most frequently used framework.

Maps: General Rules of Thumb 1. Everything has a geography. Anything that is built up from multiple unique components-whether those components are cities and rivers or concepts and ideas-can be mapped. The task for the visual thinker is to ask, ”If these ideas (or nouns, concepts, elements, components, etc.) were nations, where would their borders be-and what roads would connect them?”

2. North is a state of mind. We're used to thinking of maps with a north-south versus east-west coordinate system upon which places and objects are plotted according to their relative spatial positions. We can make maps of most anything using other pairs of opposites: good-bad versus expensive-cheap, high-low versus winners-losers. In fact, the only challenge with most maps is coming up with a meaningful coordinate system; once it's in place, plotting in the ”landmarks” is easy.

3. Look beyond the obvious hierarchy. Traditional (hierarchical) org charts are wonderful tools for mapping the official chain of command of an organization and for showing who is responsible for what. But when it comes to understanding where the less obvious-but usually more powerful-political connections really are, a bubble-based or connections-based ”map of influence” is the better tool. The data to create such a map is always much harder to collect, but the effort pays off when insights into the inner workings of an organization are needed.

Once again, back to SAX Inc.: We know from the codex that a where problem demands a map, and as we run across the SQVID we think simple, qualitative, visionary, individual, and as is. We see that we'll need to create a picture somewhere between a concept model and a treasure map showing the structure of the company. We also know that the best way to start a map is to draw in the most prominent feature, which in our client's case is their ma.s.sive accounting department, the ”factory” of their entire operation.

We start the map of our client's business structure with their most prominent feature: their huge accounting operation.

Even though that's where all those accountants sit, we now know that accounting is not the home of our new target buyers, so let's branch out from there and add in the other divisions.

The main accounting factory is surrounded by administration, sales, and support divisions.

We also know that all those groups are run like little fiefdoms, so let's add in the borders to see who b.u.t.ts up against whom-and who doesn't share any borders at all.

Adding borders shows us that sales is an independent state run by its own rules, while operations, accounting, and support share many common borders.

In the real world, adjacent nations are connected by roads, and the same is true with our client. Let's get one of our own salespeople-someone who knows how things really run over there in client land-to help us map in those interdepartmental pathways.

Based on the insights of our own salespeople into the client's organization, let's map in the roads between departments.

Hmm: No roads between sales and accounting. No direct connections means little influence one way or the other, so it's unlikely either is influencing the buying decisions of the other. OK, we've got our map. Now let's see where the treasure is.

X's mark the spots where treasure (the people who buy our software) is buried.

We've now got a sense of the divisional structure of our client. That gives us a useful overview, but as we look at it, we realize that what we really need to see is the hierarchical connections between those domains: Who decides what and who influences whom. So let's make another map of the same ”geography,” but this time we'll focus on the real power-the people. We'll approach things in the same way, starting with the most prominent feature: in this case Marge, the CEO.

We start a map with the geography's most prominent feature, so begin with the CEO.

Since we'll be showing everybody else relative to Marge, we need to establish a coordinate system around her, some place to map in the next most prominent features: Mary (who runs sales) and Mildred (who runs operations).

Two lines establish our coordinate system and allow us to start mapping in other people.