Why Projects and Budgets Have Fluff - a Lognormal Explanation

Tuck Wallace, the company's CFO, was calling her. She could see it on the Caller ID.

"This is Mei" she answered. Protocol dictated that you never acknowledged that you knew who was calling, even if you did.

"Hi Mei, it's Tuck Wallace" he said, also following protocol (he knew everyone had Caller ID too!).

"Hi Tuck, sure hope you weren't involved in that massive freeway tie up due to the bad weather"

"No, thank goodness. I come in from south of the city and the problems today were mostly north of town. Did you?" he asked.

"I'm usually in before there's too much traffic, so it was a little slow today but manageable. What can I do for you?"

"How soon do you think before you get a complete set of numbers for the budget?"

Mei laughed. "Tuck, I thought you knew better than to ask a question like that!"

The lognormal curve, one of a class of assymetric statistical distributions, has many uses, but only rarely do we get to use it to understand our company's communication and behavior.

The Twin Tension

Eliyahu Goldratt, a pioneer in the management system known as the Theory of Constraints says that a manager needs to guard their reputation within the organization against two things - being considered unreliable and being considered uncredible.

The consequences to this are dire for the person. If we are unreliable, then when the big, skill-developing, challenging, and high-impact projects come along, we will not get picked for them.

If we are not credible, then we are in a situation similar to the "Boy Who Cried Wolf" - we are not believed even when we should be believed, because our reputation has preceded us. Thus, our insights, advice, and analysis will be ignored during the company's decision making process, eliminating our ability to impact the organization and/or our industry in any meaningful way.

Once these labels have been placed it is difficult to get them removed.

Which leads us to the conclusion that the best state of affairs is to avoid getting them stuck to us in the first place.

But why is reliability and credibility a tension?

The Project Manager's Dilemma

The situation Mei finds herself in at the opening of this post places us in the right context - how long do we tell someone it will take us to complete a task?

Simple question.

Simple answer? Not so much.

Estimates of time to completion are critical factors during the project management process. Many of the project manager's tools - Gannt charts, critical paths, completion timetables, schedules, bottleneck flags, milestones, etc. - rely on these estimates for the various tasks that make up the project.

Consequently, project managers (such as Tuck Wallace is if we view the budget to be a project) are obsessed with the status of task completion and the timing of it.

According to Goldratt, if we say it will take 10 days and we get it done in 2, we will lose credibility. If it happens a couple of times, people receiving our estimates will begin to shade them back in their minds - "the last few times they said 10 hours and it took them 2, so they said 5 this time so it will probably take them 1"

In this situation, even if the person does it in 3, they will be considered late since the project manager was expecting 2, even though it was within the estimate of 5 that was given!

Similarly, if we say that it will take us 5 hours to complete the task, and it takes us 10, then we will be considered unreliable. "Those guys are always late" "We can never believe their estimates"

One of the wrinkles in this process is that the estimate range is not normal, but skewed. Time cannot be negative ("it will take us -2 hours"), so rather than being able to think about things from an evenly balanced, plus or minus, viewpoint we are faced with an unbalanced situation.

The problems will all occur on only one end of the range. If things go well, the time doesn't change that much. But if one thing goes bad, and then another, and then another, then the time to completion is dramatically increased.

Lognormally Speaking...

This skewness in results means we can picture this estimation process using the lognormal curve.

Figure A

Lognormal Time Estimates

Figure A shows a lognormal curve based on a normal distribution with a mean of 1 and a standard deviation of 1. There are several items of interest in this. Let's say that this distribution is our estimate of time to complete a task.

The median value, 2.72 days, is the "pure coin flip" outcome. There is a 50% chance of being higher and 50% of being lower.

Do we provide this estimate?

Under Goldratt's paradigm, we essentially seal our fate one way or the other. We have a 50% chance of not being credible, and a 50% chance of being unreliable - neither a very good outcome!

The average of this distribution is 4.48 days. The fact that the average is so much higher than the median reflects the fact that there is a long tail on the right side of the distribution but not on the left. Things can only be so good, we can get the job done this instant but not any sooner, but if things go bad it can take a really, really, really long time.

Do we use the average as our estimate? In 69% of the cases, we will be below this estimate (and hence not credible in the future).

The shaded regions of Figure A show the values of the bottom 20% and top 20% of the outcomes. There is a 20% chance we will take less than 1.17 days to complete this task. We could say it will take at least 1.17 days and be right 80% of the time, though this merely provides "a floor" for our estimate, and does not give the project manager anything meaningful to put into their software for task completion.

We could also say it will probably take less than 6.31 days, and likely come inside that mark. With the wide range of possible outcomes significantly below that, our credibility factor will again be at issue if we use this approach.

Finally, we could use the bottom and top to establish a range - "In the majority of cases, we will get this done somewhere between 1.17 and 6.31 days". We would be within this range over half the time, so the odds are slightly in our favor of being credible.

The big problem with the range approach is that the people hearing it do not like it. A single number needs to go into the software, or a significant event or task needs to be scheduled for a certain date.

An example of this would be booking a conference room at a hotel for the project team after a certain milestone has been completed. They simply can't call up the hotel and say "We'd like to reserve a conference room, can we come sometime between this Monday and next?"

So instead, upon hearing a range, the person gets frustrated and exasperated and says "Just tell me the answer!" and, as they are saying that, the 'thought bubble' running through their mind goes "they are trying to avoid being pinned down to something, they do not want to be held accountable, therefore they must be a slacker. I must continuously watch this slippery character."

Again, not good for our "brand" no matter if our estimate is correct or not.

The "Solution"?

There is a common way to avoid this dilemma.

Step 1: We determine an acceptable "risk" of not meeting the estimate and provide that amount. In our Figure A example, let's say we want to have 80% confidence, so we say it will take us 6.31 days.

Step 2: we do the work.

Step 3: if we get our work done before our estimate (which will happen 80% of the time), we wait to deliver it at some point close to the estimate we provided.

In essence, we establish enough "cushion" in our estimate in order to protect ourselves most of the time. In this way we avoid being labeled unreliable and uncredible!

Changing Perspective

How does our ideal solution look from the organization's point of view?

If we assume our project task is one of ten that make up the project, and all the project steps have the same distribution as Figure A, then there is a lot of waiting time that has been "baked in".

For our task, which we will deliver in 6.31 days, exactly half of the time we will have gotten it done in 2.72 days, so there is just about 3 and 1/2 days of waiting. Multiply that figure by 10 for the number of steps, and our project could be done a month sooner!

For those of you who have read Cholesky to the Rescue, you might remember that when we combine statistical distributions the standard deviation is lower for the combined outcome vs. the single outcome, so perhaps it is not as bad as all that.

In order to compare outcomes between a "deliver when finished strategy" and the "cushion strategy", we simulated in R this ten step process, assuming in the first that tasks were delivered as completed and in the second they were delivered in 6.31 days unless they took longer. We further assume that all steps are not correlated (thus no Cholesky required).

Figure B

Days to Completion

Probability of completion of project. Days to complete a project is consistently higher except at the very extreme upper end.

Figure B shows the outcome of this simulation by plotting completion times in sorted order. Convergence of the two lines (i.e. when the completion time is similar), occurs less than 1% of the time, and in fact the Cushion Strategy never is less than the Deliver When Finished approach.

Figure C shows the R output of the statistics for project completion times. The difference between the two is about 30 days no matter whether we use the median as the average or the mean.

Figure C

Days to Completion Comparison

The "Cushion Strategy" is about 30 days more than the "Deliver When Finished" approach when comparing on both median average and mean average basis.

The standard deviation of the series is slightly lower for the Cushion approach, which is not at all surprising since the vast majority of the times each task has a constant 6.31 day completion time. The standard deviation of the Deliver When Completed approach is 18 days, which is much less than the 5 day standard deviation for each individual task multiplied by 10.

Thus, from the organization's point of view, this cushioning adds waste and inefficiency into its performance.

Budget, Shmudget

We have seen how the act of adding cushion, essential to the individual's political survival, adds to organizational inefficiencies.

It is also financially inefficient as well.

Why?

We can 'transpose' the dynamics of the time to project completion estimates just discussed to budget estimates. When using the 'transpose' term we are thinking about it in a musical context - if we first sing "Do Re Mi" in the key of C, starting at that note on a piano, we can then sing it in a different key, such as G, starting at that point on the piano, and the melody is still recognizable as "Do Re Mi" (just a little higher or lower). This occurs because the steps between the notes are exactly the same no matter where it is played - we have merely started the sequence at a different point on the piano.

Likewise, the steps in the budgeting process are similar to the project time estimation process in a number of ways:

::From a cost perspective the numbers cannot go below 0, meaning our distribution will be lognormal or otherwise skewed.

::Since there are generally consequences to not hitting budget - such as low bonuses, loss of jobs, etc. - people are inclined to 'cushion' in order to prevent these downsides.

::There are the same negative reputational consequences - loss of credibility and reliability. Once we deliver 10% under our budget for the year, our budget estimates for the next year and every year thereafter get shaved back from our original proposals.

::Life is a lot harder once we go over budget. After we break through that threshold, every additional expense is intensely analyzed, reviewed and questioned - "Hey, you don't really need to read the Wall Street Journal, do you?"

Figure D

Budget Estimates

Figure D shows a lognormal curve for a potential budget scenario. This curve was created with a lognormal average of ♢ 10 million (for new readers the ♢ symbol stands for Treasury Cafe Monetary Units, or TCMU's, a currency freely exchangable with any other currency at any exchange rate of your choosing) and a standard deviation of ♢ 2 million.

This curve is less skewed than the labor estimate one, with one of the results being that the mean and median are much closer together (in a normal curve mean and median are the same), but the skewness is still there. From the median to the lower 20% is a difference of about ♢ 1.5 million, while to the top 20% it is ♢ 1.8 million.

And this is part of the lognormal lesson - the more cushion we need, the further out the curve we need to go to get it, because of the assymetry on that side.

Rather than simulate this as 10 equal steps, we can think about this in terms of proportion. If we are cushioning at the 80% level, we have about ♢ 1.8 million. This is about 18% of the median. We can then apply this to the total budget - if it's ♢ 100 million we have ♢ 18 million of cushion, if it's ♢ 500 million we are likely to have about ♢ 90 million.

That is a lot of cushion!

Furthering the problem is that cushion is unlikely to be spent to serve major organizational objectives. Since the point of cushion is to buffer our margin of error, we can't let others know it's there, otherwise we are back to the original unreliable / uncredible dilemma. So if we are spending cushion it cannot be anything too noticable. So objectives such as share buybacks, new growth investments, etc. do not benefit from this approach. Things such as Wall Street Journal subscriptions do.

From the CFO's point of view, this dynamic translates to the external communication function as well. The market's reaction to earnings surprises also reflects an assymetric tendency, where negative ones are reacted to much more than positive ones (for further info see this research paper by Skinner and Sloan at the University of Michigan). We can interpret this using Figure D - "if they cushioned, things must be so bad they wound up in the shaded regions".

What Can We Do?

It is tempting to say "let's get rid of the budget" as a response to the above. However, since a lot of organizations rely on budgets as part of their governance process, this is not always a realistic alternative.

Part of the difficulty here is that by adding these cushions we are in some respects lying. We believe we will deliver things inside these numbers the vast majority of the time. And, should we be successful at that, we are going to pretend we didn't so far as anyone else knows.

So what other things might we be able to do?

Blame it on the model - if we use a model to calculate our estimates, and we let everyone know it, sometimes we are able to attribute estimate errors to the model usage. "The Black Scholes formula really did not do a great job of forecasting office copier expense this year". This is similar to the division President attributing the Net Income shortfalls to "Allocated Overhead", which is based on a complex methodology nobody understands.

Tolerate ambiguity and uncertainty - underlying the topic of this post is the fact that we need to provide estimates that people can rely on. This is fundamentally impossible, since none of us can predict the future. The more uncertainty that we can tolerate, the more we can accept ranges of possible outcomes without needing to know the answer. After all, the only certainties in life are death and taxes, right? So in the case of budgets and projects, just suck it up and deal with the fact that there is uncertainty.

Don't tie negative events to the estimation process - if we do not get a bonus if we go over budget, the more cushion that budget will contain. If we separate the budget process from the organization's carrots and sticks, the less need there will be to add cushion. We can have more open, frank and candid dialogues about the driver's of the numbers, which ultimately are the items that need to be managed.

While the actions above will work more often than not, by far the best thing we can do is:

Establish a great working relationship with others - budget and project estimates are few and far between in the grand scheme of things. If we demonstrate reliability and credibility in our ongoing relationships, day in and day out - with our bosses, those upstream and downstream in our workflows, and everywhere alse that we can - then an occasional blip here and there, for a good reason, will be forgiven because of the strong relationships we have established. However, a relationship is one that is reciprocated. We can have a great relationship with someone, but if that someone will 'throw us under the bus' if it serves their interests, then the relationship can only be developed so far.

Take the time to explain - if we sit down with the other and 'step them through' the thought process and modeling that have led us to the conclusion we've arrived at, we provide them a number of opportunities: appreciation of the seriousness with which we have responded to their request; ability to ask questions about the process, information generated and the results; and a tangible experience of the train of thought that we ourselves have experienced. Because this has occurred, they are in a much better position to understand why things might come in better or worse than originally estimated. They no longer intepret the event in terms of our credibility or reliability, because they themselves had originally come to the same conclusion themselves.

Key Takeaways

In order to be impactful, we need to maintain a reputation of credibility and reliability within our organization. Tasks that require estimates, such as projects and budgets, are ones that can potentially undermine this reputation. Understanding the skewed nature of the estimation process helps us manage these potential impacts.

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Questions

::What are actions you have been able to take that made your estimates easier to deliver?

::What suggestions would you give to Mei to help her answer Tuck's question?

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Is the CFO's Organization a Professional Service Firm?

"All of my directors seem to want to promote people, but this just isn't realistic. If they have their way pretty soon we'll end up as an organization of managers with nobody to manage!"

Aisha Sarin, VP of Human Resources, listened patiently as Tuck Wallace, the company's CFO, discussed his current staffing situation.

"Do you need more managers, Tuck?" she asked.

"No, I really don't think we do. What's that saying? Too many cooks in the kitchen spoil the soup?"

Aisha smiled. "Yes, something like that. I'd like to understand the situation better. Sometimes managers feel as if they do not have a lot of 'tools in the toolbox' when it comes to rewarding great work, but there are also instances where people who can truly perform at the 'next level' are held back...or not challenged enough."

Tuck thought for a moment. "Probably a little of both in this case, actually. Where do we go with this?"

In prior Treasury Cafe posts we've discussed adopting the viewpoint that our finance organization is an independent company (see A Matter of Perspective).

Thinking in this way changes our viewpoint. If that snarky remark we heard yesterday came from our boss, we might be de-motivated, resentful, and dis-empowered, and our thought bubbles might read "After all I've done...", "what a %*#@", "I'm not paid enought to take this kind of crap", etc.

When that same remark comes from a customer, we attempt to identify potential problem areas and invent ways of providing even better service. We think "there is some kind of problem that needs to be solved here because my customer is unhappy".

A much more productive approach.

If we are to regard our finance organization in this light, is it possible that there are lessons we can learn from the employment models that are used in professional service firms?

How Many People?

David Maister says there are three levels within a professional service firm: "Finders, Minders, and Grinders".

Figure A

Personnel Requirements Equations

The number of each level of personnel is determined by the number and length of projects, time requirements per project, and the utilization rate of that persons time

These names come about because the partners, who are the seniors in the firm, usually are responsible for finding the business, the mid-level pros are the ones who manage the various projects and engagements (thus the minders), and the junior / entry-level folks are the ones plugging away on specific project tasks.

How do the economics of this model work?

Figure A shows the equations that go in to determining the number of personnel required in the firm. The number of projects the firm has each year and the length of each project determine the number of project hours the firm has. For a given project a percentage of time is required for each level. Finally, each level has a certain number of 'billable hours' capacity. These factors, when combined, allow us to determine a staffing level.

Figure B

Personnel Requirements Calculation

The average project takes 3 months. On a 50 week per year basis, and 40 hour work week, each project takes 500 hours. At 12 projects per year, there is 6000 project hours per year. Each project requires 50% of a Sr's time, 1 Mid-level and 3 Jr's. Each level has a certain amount of time available for projects per year, which is the annual project capacity. The required time for each level divided by the per person capacity yields the required number of personnel. In this example, the firm requires staffing of 2 Srs, 4 Mids, and 10 Jrs.

Figure B shows a calculation of the personnel requirements based on the equations in Figure A. The firm has 6000 project hours per year.

Each project requires 50% of time from the Sr level. so the firm needs 3000 hours of time from people at this level. In similar fashion, it needs 6,000 hours of Mid time and 18,000 hours of Jr time.

Based on the utilization rates for each level, this translates into 2 Srs, 4 Mids, and 10 Jrs for the firm.

Whenever we are creating a framework for analysis it is helpful to "calibrate the model" - which is analysis-speak for asking "are we getting the answers we think we should get?". In other words, if I enter "2 + 2" does the model give me 4?

In Figure B we use the same project time requirements and utilization levels as in Maister's example, and end up with the same ratio of Mids to Srs and Jrs to Srs as he did, which should give us confidence that we got the equations right in Excel.

Now that we have established the method for determining staffing levels, we can now turn to the issue of what happens through time.

Evolution

"Ultimately, the rate we promote people depends on two things - the number of people leaving the firm due to retirement, etc. and the growth of the firm" Tuck opined.

"Yes, that is essentially right, Tuck." Aisha replied. "The only other thing might be if the type of work changes. This can impact the mix sometimes as well."

"I see your point Aisha. I can think of that in terms of the span of control. Some people have 3 direct reports, others have 10, which is somewhat determined by the nature of the work they perform."

Nobody is going to want to remain a Junior forever.

At some point they expect to move up. At some point their employer expects them to move up...or out.

Employers don't want Juniors forever either.

In Maister's example, an average of 4 years is the point of progression. He uses 80% as the transition rate for Jr to Mid and 50% for Mid to Sr.

Using the information in Figure B as an example, that means we will eventually have 4 Srs (the original 2 plus 50% of the 4 Mids) and 8 Mids (80% of the original 10 Jrs), and have to hire 20 new Jrs.

A very important point - in order to sustain this rate of advancement we need to double the number of projects!

If we do not grow the business, then the Mids will not become Srs. Presumably, they will become Srs somewhere else.

The Jrs, seeing that Mids do not move up but all move out, will likely begin spending some of their time finding new gigs as well. What's the point of becoming a Mid if it is a dead end?

So the critical issue here is that firm growth and employee advancement are inextricably linked. Without one you cannot sustain the other.

A benefit to establishing the equations as we did in Figure A is to help us determine these factors. Because we have a set of equations, we can use mathematical techniques to assist in our understanding. In this case, because we are concerned with change, we can borrow from calculus and use the derivatives of these functions to help us determine the dynamics of progression within our firm.

Figure C

Rate of Personnel Change Due to Projects

The required number of personnel will increase or decrease for a given change in the number of projects is determined by the length of project, the time requirements for a project at that level, and the utilization rate of people at that level.

Figure C shows the derivatives of the Figure A equations with respect to projects. They answer the question "how does a change in the number of projects impact the number of Srs, Mids, and Jrs required by our firm?" The absence of any exponents indicates that this is a linear relationship. Using the numbers in Figure B, an addition or subtraction of one project requires a change of about 17% Srs, 33% Mids and 83% Jrs.

We can use this information to calculate a growth requirement. If we want to move someone into a Midlevel role (without any transition of current Midlevels), then we need to add 3 projects (since each project requires 1/3 of a Midlevel) to our existing 12 - a 25% rate of growth.

We can extrapolate this math further. Say we know our firm is growing at 10%. This implies that by the end of the next year we will have 13.2 projects (10% increase from 12).

Figure D

Midlevel Staff

Horizontal lines are current Midlevel staff and current Jr staff. At 10% growth, it will take 15 years to promote the entire batch of current Jrs to Midlevel.

Figure D shows the number of Mids required at 10% growth through time. In the first 8 years, we will need 4 additional ones, a promotion rate of 1 every 2 years. It will take about 15 years to promote all Jrs to Mids at this rate of growth, an average of one promotion every 1 and 1/2 years.

The information generated by this basic model helps provide insights as to how our organization will evolve through time. Will it be helpful to provide some additional dynamics?

Bells and Whistles

"I understand that the project model provides some insights as to how our organization will progress, Aisha. But it is a little simplistic."

"What are you thinking about that makes you say that, Tuck?" Aisha asked.

"Well, for one we have not accounted for migration out of the firm. People eventually retire, or their spouse gets a new job thousands of miles away and they need to relocate, so positions can be generated by this as well."

"Yes, I see your point. Some people move out of finance to other areas of the company as well, don't they?" she queried.

"Absolutely"

"Perhaps adding a factor in the model can account for some of these issues?"

Whenever we are creating a model, it helps to keep in mind that all models are wrong. The purpose of a model is to provide a framework of understanding in the most economical/efficient/simple way possible.

We cannot perfectly model reality - there are too many factors. To do so we would need to get to the level where we are simulating "butterfly movements in China" (to use the chaos theory metaphor that a butterfly's movements can create hurricanes on the other side of the world).

Every model is a tradeoff between the benefits of the information produced and the costs (time, maintenance, etc.) required to produce it..

Figure E

Incorporating Additional Information

The number of Srs required is the change in projects plus a probability factor that attrition occurs amongst the currrent staff.

Should we decide that the costs are worthwhile, we can consider some of the following options.

Figure E shows a modified personnel requirement equation which has included an attrition factor in addition to the change due to change in number of projects. As noted in the conversation above, there are a number of factors that will create attrition. The probability factor for the equation can be based on historical experience, a forecast by company personnel or 'experts', an industry average, or on some other plausible basis.

Another possibile approach would be to create the basic model at a lower point in the organization, and then aggregate it up to the CFO level.

Maister suggests that there are different types of projects, some requiring more execution, some more diagnosis, some requiring lots of contact with customers, others requiring little. Each of these project types will suggest a different construction of the different levels of time required. Thus, one department might be at the 50%/100%/300% ratio as the example in Figure B, while other departments might be at 100%/100%/100%. So we might assess the organization as a compliation of several different organizations rather than doing it as a whole.

Figure F

Disaggregation of Staff Requirements

Staffing requirements for a CFO organzation with 6000 hours in total divided into three types of activities with various staffing requirements. Total requirements are 3 and 1/3 Srs, 3 and 1/3 Mids, and 5 Jrs.

Figure F provides an example of a group with different staffing requirements for each project.

Another modification we may wish to consider is the number of levels. In large corporate organizations the division of roles may be different than the three-level system Maister considers.

For example, there may be one to four levels for individual contributors, and then several levels for managment afterwards (supervisor, manager, director, etc.). Some firms consider separate tracks, one for management and one for specialists, each with a separate level system. Adding layers and levels helps to customize the professional service firm model to our own particular organization, though again at the cost of additional modeling complexity.

What Can We Do?

We can improve our organization using the professional service firm employment model in a number of ways, such as:

Change Perspective: View Your Organization as a Series of Projects - the fact that the basic model derives from a professional service organization can sometimes throw people off - "But I do not have 100% projects". Some of this is a matter of interpretation. If our accounting organization closes the books every month, we can look at this as a routine process or reoccuring procedure, or we can consider it as a successive series of projects. Each month closing the books is a project, with certain requirements, certain actions, and certain desired outcomes. The fact that it is repeated does not necessarily invalidate viewing each one as a separate project.

Inventory Our "Projects" - breaking each of our organizations projects and tasks down to a specific allocation of time requirements from the various levels will allow us to understand where the time demands occur. Where is the greatest number of Jrs required? Srs? Understanding this can help us to determine different career path patterns within the firm. Jrs might rotate from a "Grinder" group (i.e. a group with a high Jr to Sr ratio) to one that requires more involvement from Mids and Srs. This would be a benefit to the Jr, even though they remain at the Jr level, because they are involved in higher order projects, and will thus be more likely to pick up on the different skill requirements of the levels above. Their development progresses even as they remain at the Jr level for a couple of more years.

Communicate Realistic Expectations - because we can assess the number of additional personnel required given a growth level, we can use this information to set expectations realistically within the organization. Going back to the state of our organization at 10% growth shown in Figure D, if each of Tuck's managers expects to promote someone every year, there is going to be a lot of disappointment. Tuck can use the analysis presented here to guide his organization to a more realistic expectation of how progression will occur, thereby nipping an annual cycle of demotivation "in the bud".

Develop Alternative Tools - Figure D illustrated that it will take some people 15 years to move up a level. This seems like a painfully long period of time. Developing alternative tools to recognize and reward people will therefore be required. Can we implement gamification elements that will make the job different from month to month or year to year? Rotation is another tool that can be used. New jobs are often considered rewards even if they are lateral from the org chart perspective. Can we create alternate heirarchies or project allocation systems? In colleges class selection is often done using a bidding system. Could we implement something similar with respect to some of our projects? People would end up working on things that are more meaningful to them, which is a potent form of reward.

Use as an Interpretation Framework - the professional service firm model can be a useful way to process information. For example, the consulting firm Treasury Strategies noted an evolution of Finance areas from one that was more transaction oriented to one that was more analytically oriented, moving from a traditional pyramid to an inverted one (see example here ). Using our framework, we can interpret this as one of moving from projects with a high Jr to Mid or Jr to Sr ratio to ones where the ratios are a lot lower, indicating that the skill sets of our organization will need to evolve and develop in order to keep pace with the demands from our 'customers'.

Key Takeaways

The professional service firm employment model is a useful perspective with which to view our organization. It allows us to identify issues that need to be addressed, such as employee transition rates, growth requirements and constraints, and as a convenient method to assess how changes in the industry and professional landscape can impact the value of our organization's human capital.

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This Strategic Control Map is Nuts!

There are several perspectives we can take on strategy.

One approach is to view our finance group as an independent business, and then deploy strategic tools to understand how to fulfill our mission and vision better (see for example “Rollin' the DICEE -Another Take on the Treasury Vision”). This is a helpful exercise that will lead to improved performance within our organization.

Another option is to take the overall organization’s perspective. This is important if finance is going to be a strategic contributor within the company. The strategic role of finance is becoming more and more important, as evidenced by books (such as “The Strategic Treasurer” and “Finance for Strategic Decision Making”), press articles, financial institution perspectives (“The Strategic Treasurer”), and top-tier finance and strategy firms assessments.

Finance is well-suited to play a strategic role due to the combination of core strengths in understanding value creation and analytics. Today we look at the Strategic Control Map, a tool to assist in strategy assessment and development.

What is the Strategic Control Map?

As discussed in our post on Return on Invested Capital, it is sometimes useful to break down an equation into separate sub-equations in order to understand some of the elemental drivers that produce the final result.

Figure A

The Strategic Control Map is a concept developed by McKinsey in the 90’s, and is essentially a visual representation of this “equation breakdown” process with respect to market capitalization.

Figure A shows the equation for Market Capitalization, which is simply the market value of a company’s equity and debt securities.

Figure B

By adding a numerator and denominator of the same term (meaning you are multiplying the original equation by 1, which does not change the result), we arrive at a breakdown of Market Capitalization into two components: Market to Book ratio, and Book Value. Figure B shows this representation.



Figure C

 The strategic control map can then be plotted with the Market to Book ratio on the y-axis and the book value on the x-axis (Figure C).

Enter Cost of Capital – Stage Right

The market to book ratio represents the market’s valuation of the firm’s investments compared to what those investments actually cost. This leads us to the concept of “excess returns”.

In finance, the phrase “excess returns” is used to describe a situation where the rate of return we earn from an investment is greater than our cost of capital.

Cost of capital represents what an investor needs to earn from an investment that carries a certain amount of risk.  Let’s look at two bonds to understand why.

Short-term US Treasury’s currently yield way less than 1%, due to the fact that they are low risk for two reasons. First, the US is a highly rated entity that has never defaulted on its obligations and has the ability to raise revenue on a large and wealthy economic base. Second, short-term debt is less risky than long-term debt because fewer things can go wrong in the next 6 months than could go wrong in the next 10 years.

On the opposite end, a 10-year Greek Bond has traded as high as 38%, because they are higher risk for reasons we have all heard about for years now. They have a weak economy and are burdening it excessively with funding demands, so there are little means to generate funds to pay off bonds. And there are a lot of things that can go wrong in Greece over 10 years compared to 6 months.

So an investor does not have one single required return. They have many different ones, and they are all related to the risk involved.  

·         Lower risk, lower return. A nice, safe, comfy short-term US Treasury? “I’m happy to make 1% on that”.

·         Higher risk, higher return. A risky 10-year Greek bond? “I need to make 38% to think about taking that one on”



Figure D

 Risk vs. Return is the basis for the cost of capital. Figure D shows this graphically. The more risk (which increases as we move along the x-axis) requires a higher return (which moves along the y-axis). Thus, the required rate of return is going to be an upward sloping line. For a given level of risk, move up the dashed line to find the required rate of return for that risk level, and notice that higher risk things require higher returns, and lower risk items require lower returns.

Enter Firm Investment – Stage Left

A company usually has a choice of several investments that it can make at any given time, sometimes referred to by cool names such as the “potential project portfolio” or “investment pipeline”.

For example, Farmer Joe’s Agricultural Empire might be considering any or all of the following investment possibilities: addition of a combine to accelerate harvesting, purchase of improved seed products, addition of a new grain silo, adding improved dryers to existing grain silos, etc.

Figure E

The investment possibilities will each have a different potential rate of return associated with them. Using the list above, maybe the combine is a 10% project, the seed products are 15%, the new silo is 12.5%, and the improved dryers is 20%.

The result of this fact is that the firm’s investment pipeline can be visualized as a downward sloping line, shown in Figure E, where the y-axis represents the rate of return (i.e. 20%, 15%, etc) and the x-axis is the project (combine, seeds, etc.).

Center Stage

So we have cost of capital entering from stage right, and the firm’s potential project portfolio entering from stage left, with the ultimate result that they meet at center stage.

This meeting is important. The firm’s investors expect a certain return on their investment given the risk level of the business. The firm has choices to make about which projects or investments to go forward with or turn down. The interplay informs the decision making.

Taking our example of Farmer Joe’s Agricultural Empire, if investors in this firm expect to make 10%, then Farmer Joe should undertake all 4 of the potential projects, as they all are expected to make this amount or more.



Figure F

 However, if Farmer Joe’s investors require 15% return based on the risk of the agriculture business, then Farmer Joe’s management should only invest in two projects, the seeds (15% return) and the dryers (20%). The other two projects, at 10% and 12.5%, do not earn enough to meet the investor’s required return.

We can depict this intersection by linking the two graphs we have previously seen together, with cost of capital providing the “connecting glue” between them. This is shown in Figure F.

The Market to Book Ratio Link

Now that we understand that a company makes decisions on various projects and opportunities that need to take into consideration the cost of capital, we can explore how this might work in the marketplace.

Case A: If we are a firm investing in 1 project that costs ²100 (for new readers, the symbol ² represents Treasury Café Monetary Units, or TCMU’s, freely exchangeable with any currency of your choice at any exchange rate you desire) and will return 20% forever after with no growth, then each year the firm will make ²20 in cash on this investment.

If the cost of capital for our firm is 10%, then using the simplified Dividend Discount Model (see “Apple’s Dividend – Good Financial Strategy?”) the market will value this investment at ²200 (20/10%). Our Market to Book ratio is therefore 2.

Case B: If we are a firm investing in 1 project that costs ²100 that will return 5% forever after with no growth, then this will generate cash each year of ²5.

If the cost of capital for our firm is 10%, then using the simplified Dividend Discount Model the market will value this at ²50 (5/10%), and our market to book ratio will therefore be 0.5 (50/100).  

Case C: If we are a firm investing in 1 project that costs ²100 that will return 10% forever after with no growth, then this will generate cash each year of ²10.

If the cost of capital for our firm is 10%, then using the simplified Dividend Discount Model the market will value this at ²100 (10/10%), and our market to book ratio will therefore be 1 (100/100).  

What we learn from these three cases is that if we earn our cost of capital then our Market to Book ratio will be 1, if we earn more than our cost of capital it will be greater than 1, and if we earn less than our cost of capital it will be less than 1.

Back to Strategic Control

Figure G

McKinsey breaks down the Strategic Control Map into 4 quadrants, as shown in Figure G. Companies in the upper left are in control, earning high returns on a large amount of investments. Companies in the bottom right are vulnerable, earning low returns on few investments. Companies in the upper right are considered vulnerable to takeover, given their smaller size but attractive returns. Companies in the bottom left need to focus on cost consolidation, as their large investment base needs to earn higher returns.

Figure H

In Figure H, we combine this quadrant view with our Project Portfolio line (shown in blue). This shows how difficult it is for a firm to be in strategic control, because there is a tension between earning high returns and making lots of investments.

From our example earlier, if Farmer Joe undertakes just its best investment, it will earn 20% and have a market to book ratio of 2. Few investments, high market to book ratio. This would place them in the upper left quadrant.

If they undertake all 4 projects (and if we assume equal value for each), they will average about 14% return, and their market to book will be about 1.4. Many investments, lower market to book ratio. This places them in the lower right quadrant.

To be in control a firm needs to find many, many high returning investments. Not so easy to do!

Using the Strategic Control Map

Figure I

For our Return on Invested Capital discussion, we used a local Chicago firm called John B. SanFilippo and Sons as our example. They are a producer of snacks such as peanuts, pecans, cashews, etc. sold under various brand names (hence this post’s title).

I looked up in Google Finance and Yahoo Finance their competitors, and created a strategic control map for this set of companies (using graphics in R). This is shown in Figure I.

Viewing this map, we can see several things.

·         First, there is one “big dog” and a bunch of “smaller dogs”.

·         Some firm’s are not earning their cost of capital (market to book below 1)

·         Evidence of the tension brought about by the Project Portfolio line is evident (higher returning firms are smaller in size)

·         Our friends at SanFilippo (JBSS in the graph) have some work to do

This last bullet I mention because if we overlay the Project Portfolio line into the graph, then the optimized tradeoffs should be on the line, so the line becomes the “most efficient frontier”.

Figure J

 We cannot be “upper and to the right” of the line because higher returning investments are not there.

Figure J shows the situation if we are “lower and to the left” of the line. In this case we are sub-optimal, we should either be earning higher returns on the investments we have made (the “earn more” direction) or be undertaking more investments at that particular rate of return (the “make more” direction).

Figure K

Figure K shows the Strategic Control Graph with the addition of what it looked like two years prior. The lines connect each firm’s current vs. previous position, indicating their progression over the past two years.

Several things stand out on this graph:

·         Our friends at SanFilippo have remained relatively constant, there is little movement within the two years

·         Both Lance (LNCE) and Diamond Nuts (DMND) exhibit movement consistent with the slope projected by the Project Portfolio line

·         Golden Enterprises (GLDC) and American Lorain (ALN) has seen their value reduced and have not grown

·         Inventure Foods (SNAK) has done something to dramatically increase the returns on its existing portfolio

From JBSS’s perspective, they need to either move to the right along the map or move upward. Given the distance traveling left to right between them and Diamond or Ralston (RAH), they would need to invest a lot of money in order to achieve this. It seems like it would be more likely that they be able to find a way to improve returns on their existing portfolio.

Alternatively, a merger with SNAK should move them up and to the right, which is the direction that you want to head on a Strategic Control Map.

From an industry perspective, it is possible that a merger between Lance and Diamond would move them to the right on the map. If they could combine this with improving returns on their product lines (either through synergies from the merger or better investment possibilities), they would be in a position to challenge Ralston for control within the industry.

Key Takeaways

The Strategic Control Map is one tool that can be used in a strategy setting to generate insights into industry performance and direction. Its usefulness is enhanced when we employ finance concepts into the analysis.

Questions

·         What does the Strategic Control Map suggest to you in the way of JBSS’s actions?

·         What insights for the industry do you notice from the Strategic Control Map?

Add to the discussion with your thoughts, comments, questions and feedback! Please share Treasury Café with others. Thank you!

5 Reasons NOT to Use the Olympics for Business Lessons

A lot of people in the world will begin devoting some of their focus and attention towards London as the Olympic games begin this week. My wife and I have our own particular favorites – Gymnastics, Swimming, Archery, and Rowing among them.

There is a lot we can learn from Olympic athletes. For example, in the prior Treasury Café series on the “Power of 10,000 Hours” we examined the need to devote serious focus and time practicing if we want to achieve excellence in our field. Over the next several weeks we will see plenty of examples of the results of these efforts. The Olympic competitor is certainly a role model in this regard.

However, we are also at risk of taking home lessons during these games that are not applicable to our organizations for the following reasons.

It Ain’t So Simple

The definitive results that games and sports provide is naturally appealing to us. Given a set of rules and structure, people compete and at the end we are able to determine an undisputed winner - Runner A’s time was 1:42:05, and Runner B’s was 1:42:06, so A wins.

Yet, we must remember that this is an artificial construct that has been established precisely so that there can be an objective determination of a winner.

In real life business is not so simple. There is neither a definitive structure nor a standard set of rules everyone follows. Company A operates internationally while Company B pursues a local niche strategy. Company A operates according to Brazilian law while Company B is subject to Hong Kong’s. The practice of business is quite different in the Middle East than it is in the United States.

Determining who a “winner” is in business is also not clear or definitive. There is no single metric that determines success like there is in the 100m backstroke, where whoever reaches the button first wins.

What metric should we choose to determine a business winner? All of the following are defendable choices: Market Share, Return on Invested Capital, Total Shareholder Return, Year Over Year Earnings Growth or Same Store Sales, Leadership Development. And the fact is that all of them are important.

More Than One Can Win

In the Olympics, there is only one spot on the podium for a gold medal winner.

Given the variability in metrics that can be employed, we can have a situation where Company A is the winner in ROIC, while Company B is the winner in year over year Sales Growth. Who gets the gold?

The fact is that each company operates in accordance with its strategy, and the success of their efforts need to be compared to that more than to any other firm. Consider the soft drink industry – Coke wins on market share, yet Pepsi operates a successful diversified portfolio that includes the dominant Frito-Lay snack line, so they might win on comprehensiveness. And while they would not medal on sales or market share, Jones Soda is still considered a successful company by many. They are all winners in their own way.

Business is as much about partnership and relationships as it is about competitiveness. It is not just being the first to cross the finish line. Sure we want to sell more products and services than our rivals, yet that may not prevent us from operating a joint-venture with them to exploit opportunities in a new market or industry segment.

In fact, we often attempt to pursue strategies that create win-win outcomes. The customer gets value and the company gets value. Talented employees enjoy working at our firm and our firm is happy to have the talent they’ve got. The M&A deal is structured in a way that both buyer and seller derive something extra from creating a larger pie. In many industries the players exhibit a large amount of cooperative behavior (e.g. airline pricing, cereals).

Nobody Has All “A” Players

The composition of an Olympic team is the culmination of an elaborate screening process. There are local competitions, regionals, and nationals that an athlete must clear to make it on the team. The folks going to London are the crème de la crème.

Yet, back here at the office, we are faced with the fact that our teams are composed of A players, B players, and C players. How best to organize and lead a team in this environment is going to be very different than an Olympic team.

Talent management is a hot topic these days, and it seems everybody wants to populate their ranks with A-players who can be developed into great leaders so our business will live long and prosper. Yet, it is a myth to think we are ever going to have a company full of them.

The fact is we need some of the other types as well. We need B-players who will perform adequately in any number of tasks and be happy to do so, and be willing to stick around even if they didn't get that last promotion. We need specialists with deep expertise in relevant domains, even if they never aspire to leadership roles.

Jeffery Immelt became CEO of GE after a 3-way succession race. The other two folks went on to become CEO’s somewhere else. A-player talent has a tendency to disperse.

There is No Ending

After several weeks, the Olympic games will be completed. We can tally up the medal count and see which country got the most golds, silvers, and bronzes. We will recount the exciting finishes, and begin to think about the next round of games (which should have been in Chicago!).

In business, life goes on. We do not have the luxury of operating for a few weeks every 4 years and spend the rest of the time doing something else while training. Day in and day out the “beer needs to get delivered” and the “sausage has to get made”.

A manager faces a dilemma that the Olympic athlete does not – the trade-off between short-term and long-term. Manager A may direct his efforts towards increasing the current year’s sales for a number of good reasons, and all their resources are directed towards this objective. Manager B, on the other hand, carves out 20% of their team’s time for development activities, projects, and other items that will pay-off in the future, at the cost of lowering this year’s numbers. Both may be correct decisions in their different contexts.

So while Olympians can expend all their effort during August, a business does not have that luxury, because we hope to be around in September as well, and we need to manage with respect to that eventuality.

It’s All About the Future

In the Olympics, the medals are the prize of the competition. The athlete gets the gold, and keeps that medal above the fireplace, locked away in a box, gives it to their parents, etc. and can have it forever. The books are updated to reflect the winners, and these will live in infamy. There will only be 1 marathon winner in 2012, and that fact will not change when it is 2112.

In the business world successes are not so permanent. The fact is, by the time we have determined that we were successful and won our gold-medal (however we chose to measure this feat), it doesn’t really matter because we are already focused on operating in the next year, where success needs to come again…and again….and again.

General Motors had the highest revenues in 1990. Does that mean investors are flocking to them because they “medaled” in their race? No? Why not? Because we do not care how they did, we care about what they are going to do.

Wal-Mart had the highest revenues in 2011, surely this is still relevant? Not really…we want to know what 2012 and beyond is looking like.

It is a “what have you done for me lately” world, and a business always has its eye on that. The goal today is to remain relevant tomorrow - by the time the results for the current race are announced, they really are irrelevant.

Key Takeaways

The Olympic games are fun to watch, and to witness top performers operating at their peak is a pleasure, yet if we are not careful we can infer more than we should as it applies to our daily lives. Make sure you take home the right lessons.

Questions

·         What lessons can you think of that might be unproductive to learn from the Olympic games?

Add to the discussion with your thoughts, comments, questions and feedback! Please share Treasury Café with others. Thank you!