Politics and Market Segmentation: Why is Trump/Sanders a surprise?

The current primary season had me thinking about market segmentation this morning.  In particular, I was thinking about how the US population is traditionally understood:

If we assume that people are basically normally distributed along this one-dimensional scale, you end up with a distribution that would look sort of like this:

Where each of those little blue dots represents some voters (the data is made up, with a random, normal distribution).  There are some way to the right and there are some way to the left, but most of them are clustered in the middle, with increasing density as you move toward the middle.  The two major parties basically jockey over where the dividing line is and try to establish their candidates to capture as much territory as possible while playing chicken on the issues they think they can slide by on.

The fundamental problem is that this market segmentation is based primarily on how American politics is organized and not on how American individuals actually think.  For example, let's assign some typically assumed attributes to each party:

Do these clusters make sense?  If I believe strongly in Christian values does that mean I have to be opposed to affordable health care?  If I think that affordable education is important, does that mean that I must also be opposed to gun control?  This is a market segmentation strategy that is "Inside Out" -- it is based on how the governing parties are organized.

Smart market segmentation is "Outside In" and starts with the criteria people use to make decisions and then organizes around that.

Instead of this one-dimensional approach to segmenting voters, let's consider some two-dimensional approaches.  For example, let's consider some classics, such as personal freedom v. national security or government size v. economic stability.

Or, let's make this very simple and assume the same old Left/Right continuum and add a single new dimension of "Anti-establishment".  In this case, I might argue that the population looks more like this (this data is completely made up):

The distribution along the X-axis is the same here as in the previous drawing.  What's different is that I now have that Y-axis to represent that person's opinion regarding the political establishment.  With a wild majority of people effectively sick of the status quo candidates and more interested in finding an anti-establishment candidate than a traditional left/right candidate.  This is why Sanders and Trump are popular.  Both of them represent a break from the traditional choice that voters are given and are a chance to vote on a different (more meaningful) decision vector.

It's easy to chalk up Trump supports as racists and Sanders supporters as crackpots -- and maybe there's some truth in each, but the reason for their popularity is that the two choices that are available fail to satisfy the buying public.

Common Pitfalls - part 2

Last time I wrote about common problems in business plans that are associated with market sizing, forecasting and especially about estimating market share.

Other common issues are associated with pricing and margin expectations, defining the target market, project risks and customer contact.

Pricing forecasts are too aggressive

We see two sides of this coin.  For established products, we rarely test the limits of pricing for product line extensions, roadmap refreshes and similar product introductions that have the possibility of increasing our asking prices.  In these cases our models will always hold pricing flat, and thereby underestimate the revenue potential.

On the flip side, for new products in currently unserved or underserved market spaces we regularly overestimate the likely selling prices.  A common method to estimate these prices is to do a value chain analysis, some sort of should-cost and required margin analysis and then to determine how much profit pool is left in the portion of the value chain that the product will displace.  This makes a lot of sense and gives a good feel for how much the product could sell for.  Then, when it's finally ready, sales has a volume quota to meet, leadership gets worried about failing to land anchor customers and everybody sort of loses their spines.  The result is that we ask a laughably low price and the customer readily agrees!  This is a real "Flaw of Averages" sort of problem -- you will never get a higher price from your customers than the one you ask.

Margins are unrealistic for a new product

This one happens when we do a lot of market benchmarking to try and estimate prices based on our expected production costs and the product margins reported by competitors who are playing in the same (or comparable) markets.  Benchmarking is a great place to get started, but eager analysts and business managers often overlook the fact that incumbent competitors have had a head start to work out their cost structures, to improve their manufacturing flows and to feel out the best price points.  Their margins probably have improved over time--our first few years will not be so fat.  Similarly, fat margins happen in low-competition environments so by our very entry, everybody will have to tighten their belts and margins all around will probably come down.

Serviceable Market is too broadly defined

Often we will do market surveys that start with a "Total Available Market" this is broadly defined and we draw our numbers from commercially available sources like IDC or Gartner, etc.  For example, if we're working on a part intended to be included in new home construction as a sort of OEM Smart Home product, we will buy research around new housing starts for the next 10 years or so.  Ignoring the fact that these reports are almost never stochastic (they almost never include estimates of uncertainty or ranges for their estimates), they also almost always describe a very broad potential market.  For this reason, we try to define a portion of the total market as a "Servicable" market.  This is the subset of that market that could hypothetically meet their needs with the product we're intending to develop.  Often this segmentation is just as broad as the Total Available segmentation and we overlook the nuances in purchasing decisions between members of that sampling.

Sticking with our smart home example, if the key features of this product are all associated with climate control (like Nest or something) then you should anticipate that it won't be very attractive to new home builders in mild climates.  You can also safely assume that builders below a certain price point (like KB) will have a much lower sell-in rate than custom builders or luxury builders (like Toll Brothers).  It's common that a business manager won't consider all this and will just say "let's just assume we can address 80% of the market".

This approach is not only guaranteed to misjudge the size of the market that we could really address, it also skips past one of the most important parts of building up a business plan; actually talking to customers.

Business Plan never learned about actual customer preferences

I almost forgot this one is on the list, and in retrospect I'm not sure how I could forget it.  This is the case where an entire business plan is built up around a perceived use for a product that we already have--it just takes some modification or rebranding--with a new group of customers that we have little or no experience with.  It can be surprising how quick people can be to extrapolate their own experiences into conjecture about a broad segment of the buying public.  Compounding this problem is that (typically) between our business plan and that hypothetical buying public is a constellation of partners, manufacturers, retailers, channels, and co-travelers, any of whom can throw up a "I don't get it" roadblock.  We should have a really good answer to that objection before we even start to get serious with the rest of these forecasts.

Project risks are ignored

For most of the analyses I see, the actual Project spending isn't material to the overall NPV of the project.  By this I mean that the amount of the NPV is de minimis when compared to the margin dollars involved.  For this reason, it's common for teams to ignore project risk when building up their forecasts.  The business development managers involved will pulse the project managers for a general idea of how long it should take to develop and how many heads will be required and some real primitive multiplication-type analysis will take place and the RnD budget for the project is roughed out.

This approach really leaves a lot to be desired.  For one thing, "a failure to plan is a plan to fail" and RND project management really needs have at least the major serial stages of development roughed out, with the parallel activities in each stage identified and some sort of risk register built up.  Even this basic analysis will often show that the back-of-the-envelope timeline proposed above will really underestimate how long the project will take.  Sometimes the project timeline balloons to as much as 2x when taken in this sort of risk-adjusted, expected value perspective.

Whether or not the spending itself becomes material, there are usually other projects waiting for those people to finish up and move on to the next thing.  Even more importantly, a product that hits the market months (or even years) after the expected launch date is very likely to experience a very different competitive environment than the original forecasts of market share and market pricing called for.  Competitors may have produced improvements to their products, new competitors or new substitute products may have appeared, in some cases the very ecosystem purpose for the product may have rendered it obsolete.

Common problems in business models - Market Share

Common Pitfalls when estimating Market Share

There are a few things that seem to pop up on a regular basis when a business analysis / business plan is being developed.  More often than not, these are the product of biases and short-circuited heuristics on the part of the analysts and business owners involved.

When I'm doing an analysis review (and especially when I'm doing a long day of these reviews) I start with this list and immediately look to make sure these problems don't exist:

Competitive environment is poorly understood

Most of our business decisions address a competitive environment in which we are the incumbent.  This sometimes trips up business managers who are looking to extend our business into adjacencies or into transformational arenas.  If the plan doesn't comprehend the current competitive situation as well as how that competitive environment is evolving, it's time to go back and break out Porter's Five Forces again.

Market share ramps too quickly

I occasionally see some really enthusiastic projections.  I mean, really enthusiastic.  For example, a brand new product, that serves a market we're not familiar with, customers we don't currently do business with, through channels we're unfamiliar with, but we'll ramp up our volume faster than the last iPhone.

Peak market share is too aggressive

I see this one a lot.  The logic seems to be "if we can't capture first place in the market, why would we even enter?"  This might be true, but it doesn't mean that we will capture first place in the market.  If the peak market share for a product introduction is not consistent with the competitive environment, it needs to be adjusted.  Similarly, if the peak market share makes volume assumptions that we can't physically produce with our current manufacturing facilities, supply chain and channel structure, it needs to be adjusted, too.

(more to come)