Allocations and Decisions

I frequently run into an issue with allocations.  Specifically, an issue with confusing accounting allocations for something that is useful in decision-making.  In accounting, allocations is:

the process of shifting overhead costs to cost objects, using a rational basis of allotment. Allocations are most commonly used to assign costs to produced goods, which then appear in the financial statements of a business in either the cost of goods sold or the inventory asset.

As an example, imagine this classic situation in engineering.  BigCo is developing a new product line.  My kid is 4 and obsessed with potty words, so we'll call it "Product Booger".  Product Booger will cost about $1,000 of RND spending to get ready for market, and once it goes to market, BigCo expects it will sell around 500 units at $20 each.  Each unit will cost $10 to manufacture.  Should BigCo do this project?

Here is the super-basic analysis

If BigCo has the $1000 to invest and doesn't have other investments with a better efficiency ratio, they should do this project.

Now imagine that a super-eager young person comes along with an idea for a product extension based on BigCo product Booger.  Product NoseGoblin is a derivative product that will cost $100 of additional RnD and should sell around 200 units at $16 each.  Each unit will cost $14 to manufacture.  It is safe to assume that NoseGoblin won't cannibalize any of Booger's sales or anything like that. Should BigCo do this project?

Here is this super-basic analysis:

So this NoseGoblin isn't as good as Booger, but it still has a positive return and recommends itself for investment if BigCo's alternatives don't have a better efficiency ratio than 1.0.

Then the accountants catch wind of NoseGoblin.  They decide that it needs to carry a portion of the shared investment from Booger.  Doing a classic revenue basis allocation--allocating the RND spending according to proportional revenue-- Nosegoblin picks up an extra allocation of $242 (at the same time, Booger looks $242 cheaper).  A few months later, a new financial analysis is performed and NoseGoblin's financials look like this:

It is now a negative financial return.  Kill it fast!  Super-eager person's heart is broken.

this what a GIS for "sad super eager person" finds for me

This is not a made up situation.  I have seen this happen.  It gets even crazier when BigCo decides that everybody needs to carry a share of overhead allocations in financial analyses, too.  Suddenly you see stuff like this:

Even though this project doesn't drive any additional SGnA, IT activities, shared technology development, new building construction, etc., GAAP rules require that these allocations get managed in the PNL so they tend to find their way into the financial analysis, too.  Load in things like depreciation, taxes (which are usually so convoluted that trying to estimate the real tax impact of a new product is fool-hardy) and you're ready to start shooting down loads of good projects that fail to meet a corporate hurdle that completely misses the point.

Accounting allocations being used for decision purposes leads to bad decisions.  When we do portfolio analyses, we keep them separate and link the spending through relationships and work hard to identify incremental spending.  Only spending that is truly incremental is relevant in the analysis.

The parable in Tsar Saltan... "Gvidon's Squirrel"

I like to tell my 3 year old stories that are loosely based on Russian Folk Stories that I found in this book.  I take down the gore as much as possible and generally try to shift the jobs that people do to be a little more appropriate for modern times (and make the animals more fit for the desert, where we live).

On story I love to tell is based on "The Tale of Tsar Saltan".  In this story, a young man (Gvidon) ends up distant and unknown to his father (Tsar Saltan).  He helps out a swan, who turns out to be a magic princess and who falls in love with him and does him all sorts of favors.  Every time Gvidon sneaks back to his father's castle in the form of a fly, he comes back with a request for some new and crazy thing that he heard about there.  One example is this one:

 "After he flew back to the island, Gvidon told the swan the story he heard about the remarkable squirrel. Then the prince walked into his courtyard and, lo and behold, there was the singing squirrel, sitting under a fir tree, cracking golden nuts! The prince rejoiced at this and ordered that a crystal house be built for the little animal. He placed a guard there to stand watch and ordered a scribe to record every shell. Profit for the prince, honor for the squirrel!"

Basically, he found himself in possession of a magic squirrel/tree combination.  The tree produced golden nuts (each of which held a ruby inside) and the singing squirrel would go up and collect them, take them down and crack them and stack the riches up in piles.

The part that I love about this story is that Gvidon doesn't just take the riches, he then builds a completely non-value-added organization around those riches.  He establishes a completely superfluous crystal house for the squirrel, he organizes and accounting department to keep score and establishes a management structure that watches the whole thing happen.  

When I tell the story, I keep going.  The guards need management, so an executive structure is organized.  The accounting department eventually branches out into strategy and financial analysis and grows headcount.  Eventually there are organizations built up around selling the rubies and the gold on international markets.  The organization continues to get bigger and bigger and bigger until eventually the tree and the squirrel are at the bottom of the hierarchy, getting bossed around by MBAs and seasoned executives who have been in this business for years.  By the end, Gvidon's entire income is consumed by the organization.

How many times does this happen in the real world?  A start-up comes out with a great business concept and develops a product that is worth buying.  People value the services or the experience and the company starts to take off.  The need to scale and they take on investors, who want to track progress.  Before you know it, it's "Gvidon's Squirrel."

(if you're interested in reading the whole story, I found an online copy here, which is where I found that picture, too. 

Bad stats -- "good enough"

I'm reading (or really listening to the audiobook during my commute) "Traffic: Why we drive the way we do" by Tom Vanderbilt.  It is a pretty good book and well researched and surprisingly interesting given the pretty dry nature of the material.

This morning, he was discussing what is a "safe road."  In particular, he was talking about small, curvy roads and whether they are made safer when the turns are labeled with reflective posts and recommended speed signs.

Proper signage is optional

Research has shown that the average speed on unlabeled roads is lower than on labeled roads.  The proposed reason is that the unlabeled road is observably dangerous, so drivers are more careful and drive more slowly.  The labeled road lulls drivers into a false sense of security and therefore they drive faster.  His conclusion is that the labeled roads are therefore more dangerous, as evidenced by the higher average speed.

Here's the thing though... average speed doesn't matter!

What matters is the occurrence of a driver entering a turn with a speed that exceeds the combination of his driving ability, the character of the turn (radius, traction, etc.) and the performance of his car.  If the "fly off the road threshold" (or put another way, "bad enough") isn't exceeded, the driver keeps right on going, no matter how close he might have gotten.  The conclusion drawn by the author is therefore baseless.

Further, if we imagine that the presence of the signage increases the average speed but decreases the standard deviation (or more specifically tightens up the distribution in one way or another), then we're probably less likely to hit the bad-enough threshold and have an accident, even though average speeds are higher.  This seems believable, since better information means that people don't have to guess how fast to go through the curve, and they should converge on something similar to the posted, recommended speed.

made with @Risk by Palisade

In the little simulation I did here, we have two distributions.  The blue represents the "no signs" scenario, where the driver has no idea what they're in for and tends to drive slower.  The red represents the good signs scenario, when everybody knows what's coming.  I set the "bad enough" threshold at 40 mph.  You can see that 0% of the good signs people crash, but 1.3% of the no signs people crash.

There is an analogous concept in marketing, called the "good enough" line.  The idea is that people have some threshold for purchase that depends on certain quality vectors.  In a car, for example, a driver might have a minimum requirement for horsepower, seating capacity, gas mileage, etc.  If your car doesn't meet that threshold, that person won't buy it.  If you exceed that threshold, they won't pay any more for the car and you don't monetize the value.  It's all or nothing.  This concept applies to lots of things.  While the car crashes when it exceeds the threshold, the customer buys something when their desire for the product exceeds the threshold.

So here's the problem.  Statistical process control (SPC) is all about removing variability.  Mass marketing and homogeneity of product offering is the way of the world.  What are the actual differences between different Android phones, for example?  As things move toward the red distribution, fewer and fewer outliers will exist in the tail, and fewer and fewer people will reach the purchase threshold for your product.

So the takeaway is that new products should desperately avoid the middle path.  If you're going to put out something new, put out something really new.  Expect most people to dislike it.  What you need is a few people who will like it, and you won't get there if you don't produce the wildly unpredictable product.

options in the wild: part II

At the very beginning, I did a straightforward ROI type of analysis.  The decision seemed very clear from that perspective.  There was one line that took a little more work to get to, but was half as long and had twice as many windows operating.  It should have moved twice as fast.  Easy choice!

I hadn't considered the uncertainty in the model.

The people in line "d" were long a call option on all of the windows to the right.  If any of the windows from "e" through "h" opened up, they could easily exercise that option by walking over and moving to the new line.  I hadn't thought of that until it happened!

Once window "e" opened up, I sat there considering moving to line "e", thinking they might open up "f" or "g" or "h" and I didn't want to miss that opportunity, even though it meant moving to the back of the line.  I decided I was pot-committed to "b" when the other option in the mix made itself known...

The crew of any plane that happened by was long a call on window "a" and "b"!  Since I was in line "b", I was effectively the counterparty and short a call on those windows.  When the crew turned up and took over the windows, they exercised their call and my line came to a stop.

This story is a pretty good representation of the value of using a real options decision framework for a couple of reasons.  The most obvious reason is the importance of involving uncertainty in your decision.  If nothing had changed, my first choice was unquestionably the best.

The second reason is the importance of having a dynamic decision framework that can adapt to new information.  It's easy to make a straight-forward ROI type decision when you ignore the changing world.  One line was served by two windows and was half as long!  That's an idiot-proof decision!  A few minutes later, the decision was more complex.  I was at the end of a line that was roughly the same length as the others, but didn't have the advantage of more windows possibly opening up.  A few minutes after that, I was at a stand-still.  A robust, options-based decision framework that encapsulated the upcoming decisions would have helped.

From an executive decision making perspective, this sort of decision tool is almost never available.  What can be available, however, is some intelligence about what the inflection points are.  If I had any idea about the chances of another window opening up, or what the chances of a crew showing up, I could have produced some heuristics about comparative lengths of each line and made dynamic adjustments to my strategy when the real world changed in front of me.

Options in the wild

A few weeks ago I was travelling on an international business trip.  On the way back I came to the top of an escalator to face the immigration / passport check area.  It looked like this:

(only the lines were a lot longer)

I just jumped into the line that was right in front of me and then sort of observed the lines.  The mental schematic I put together was this:

So I moved through the crowd to line "b" because it was the shortest one I could join (since I don't hold a EU passport).  Also, I realized that there were to windows serving that lane... both window "a" and window "b".  No wonder the line was shorter!

A minute later, the situation looked like this:

As the efficient, German airport had recognized a long line and opened window "e" up, and a mad dash had taken place as people near the end of the line for window "d" scrambled to be at the front of the new line.  My old location at the end of line for window "d" would have put me in pole position for the newly opened window!

Then, a minute later, this happened:

When the crew for some flight showed up and took over priority on window "a" and window "b".

Being a ridiculous person I thought "This is fantastic!  What a great example of real world options analysis!!  I can't wait to write this up!"

What are the options?  Take a few minutes to think about it.  In a few days, I'll publish my thoughts on it, but I would really like to hear what others say, too...

Visualizing your business model

The elements of the business model

If you haven't read my last post about the elements of the business model, do so now.  There's not much sense in reiterating what a prospect is, or how it fits with a product, etc.

Now, check out this picture:

The visual business roadmap

There is a great deal of information in this drawing.

Along the bottom you have the projects associated with your technology (product development) roadmap.  In the drawing I have here, you have two layers--real business can have many more, of course.  The bottom row represents core technology programs.  The layer above that represent product development projects.  Each product development project relies on one or more core technology program.   This is very typical.

Along the left side are market development projects.  These projects are intended to change the appetites and buying behaviors of the markets in general--whether or not you will capture the business produced.  For example, when Apple introduced the ipod the TAM for portable MP3 players exploded.

Along the right side are all sorts of projects.  In a real portfolio this is where most of the decisions really are.  These projects can be things like customer enablement programs, directed marketing programs, and anything else that will impact your expectations around your prospect.  That is to say, anything you think will impact the market share and/or pricing expectations for that product with that market.

Often a project will have impacts at multiple elements of the drawing.  

For example, adding a cool, new feature that has never been seen before may encourage people who would never have bought a product like yours to enter the market (TAM expansion), will help you increase your share of that newly expanded market (MSS expansion) at an increased price (ASP increase) but with the downside of an increased product cost (Cost increase).  In this case, you would be impacting markets, products and prospects all at once!!

modeling your business - projects, products, prospects, markets

What are the fundamental elements of modeling a business?

I often help people figure out how to model and value their business concepts.  A really common concern is "My business is different!"  That rallying call often serves as the number one roadblock people have when trying to build a business analysis.

The fact is this: No matter how different your business is, it's different in one of the same few ways.

All businesses expect to have customers.  All business hope to deliver something of value to their customers.  All businesses do some up-front work in order to have that valuable thing and to make sure their customers know about that valuable thing and to actually deliver the thing to them.  Whether the thing is physical (like a car, a microchip, a refrigerator, a satellite or a pencil) or a service (like a hair cut, consulting, vacation experience, healthcare), or something intangible like software doesn't matter.  The fundamental economics are the same.

If your business doesn't look like this--well you don't really have a business.

So let's take that "my business is different" issue another step.  How is your business not different?

Products

You have (or will have) something that you want to sell.  If it is a tangible, physical product, it probably has some sort of manufacturing cost associated with it.  You should get an idea of how much each unit you sell will cost to produce and deliver to customers.  This is the variable cost of manufacture, or "unit cost" for short.  Unit Costs will sometimes scale as a function of learning curves or economies of scale, and sometimes they'll just stay flat.  Sometimes (like software) this number will be zero.

Fixed Costs

In addition to the variable cost of manufacturing, you'll have overhead.  Maybe you need to build a factory in order to produce your product.  Maybe you need to build a brick and mortar store as a venue for providing haircuts.  Whatever it is, you will have some fixed costs.   This is often called PPE for Property, Plant and Equipment.  PPE will almost always scale with your expected volume, but with the critical distinction that you have to make your investment in PPE before your volume starts to realize.

Projects

Your business will probably require some spending up front that doesn't go into PPE.  Sometimes this is called RND (Research 'n' Development), sometimes it's called NRE (Non-Recurring Engineering), sometimes it's just called "Spending".  Whatever you call it, this is what you have to invest in time and people-hours and other expense items in order to get to the point where you're ready to start bringing your product to your customers.

Markets

You have customers who are (presumably) going to find your product valuable and pay you for it.  Smart companies undergo an exercise called "Market Segmentation", where they try to group their customers together into meaningful groups called markets.  Members of these markets have similar buying behaviors.  They typically value the same aspects of the products and are willing to pay similar amounts.  For purposes of business forecasting, you should take an "outside in" look at your markets and a great deal of your analytical work will be done just trying to size these markets.  How many potential customers are there in each market?  How many of them will make a buying decision in any specific quarter (or year)?

Prospects

To build a predictive business model you need to make forecasts about how well the products you're creating will be received by the markets you have characterized.  This is a "Prospect" -- the specific economic expectations for an individual product with an individual market.  You will spend most of your business analysis time on forecasting prospects.  When will this product hit this market?  How much market share can we hope to achieve?  How quickly do we think we will achieve our peak market share?  How long before we see that peak share get eroded away--either cannibalized by our own subsequent products or defeated by competitive ones?  What sort of prices will we be able to command for the products?  How will the price and the market share forecasts interrelate?

These are the fundamental elements of analysis for any business.  

Before folks should start thinking about how their business is different and how their model won't fit into a typical analysis, they should address these questions and frame the business through these lenses.  After these basics are sorted out, you should start worrying about things like competitive timing, synergies and roadmap effects, market saturation and disruptive effects, complex pricing structures and so on.  Normally those sorts of details won't move the needle on the big analysis.

This isn't to say that the more detailed analyses aren't necessary.  If you're in the middle of negotiating tiered pricing discounts with an important customer you should really figure out what those will mean to your revenue and NPV expectations.   Those things can wait until later.

Next time I'll put up some materials one the mechanics of using these essential entities to create an NPV.

Will your project survive in a big company?

This is based almost completely on work by this guy:
http://www.thomasthurston.com/

He found 8 questions that will effectively predict whether your new business line will succeed in a large organization.  I've paraphrased them and reworked them a little according to my experiences.  It has been a while since I've seen the originals...

1. Are the margins big enough to be interesting?  (Interesting >= current margins)
2. Are the markets you're serving big enough to be interesting? (Revenue contribution >= current revenue * 1%)
3. Does the project help sell products the biz is already selling?
4. Is the product in a market category we already participate?
5. Does the program help combat a top competitor?
6. Is the target market available through current primary channels?
7. Is there no perceived threat to an existing top customer?
8. Is there no perceived threat to an existing, power internal group?

If you can answer "YES" to everything, congrats!  You may survive the business funding cycle!

If you score one "YES" you're looking at a 50/50 chance of surviving each funding cycle.

If you score two "YES" answers... well, forget about it.

You might have a great business concept, a wonderful go-to-market strategy, and competitive products that serve a real market need.  If the corporate anti-bodies are going to reject you... you'll be rejected.

I have seen this happen several times.  There are reasons for a lot of this behavior.

For example, if this margins are too small, it will drag down the company's margins and starts to look like a growth trap.  From a strict-finance perspective, you're lowering the effective return for shareholders.

Most of what you see there are questions that are associated with diversifying the business.  Expanding into new markets, serving new customers (or pissing off old ones), attacking new competitors, etc. -- these are all outside the core and scary and difficult to do.

This is why big companies often fail to thrive.