Friday, August 30, 2013

Don't let the bike rack hit you in the face

On Tuesday night I went roller blading with a skating group I have just rejoined as I had been told Tuesdays was an easy skate. Unfortunately most of the people on the skate were training for a long road skate, and so decided to make the evening an hour and half of hill work. 13 miles later and totally exhausted I skated up to my car which had my bike rack attached to the trunk. I opened the trunk, sat down, took off my skates and pads, stood up and closed the trunk. The rack hit me in the head and left a mark.

As I licked the wounds to my ego, I thought about what had made me close the trunk standing where I was, while the rack was attached and I knew it was there. Basically tiredness. We read about many accidents occur when people are tired and not focused on what is around them rather than what is right in front of them.

Reflecting on this I thought of what I see around me in the corporate world today. I meet so many CEO and corporate employees at all levels who are working flat out to keep up with the work load they have. This is a result of many companies laying off people and distributed the work load in order to increase the bottom line.

All the people are working diligently but when you talk to them they tell you they are tired and overwhelmed. Just the right condition to close the trunk on yourself. My concern is what happens when the unexpected happens. Will they see it coming and prepared, or will it be a huge surprise and when it does hit will they know how to deal with it or will it just overwhelm them.

Things work and we can go flat out, heads down, when we our environment is in a steady state; however, the world doesn't seem to follow or allow for steady state conditions for any long periods of town. The change often starts and grows and is not noticed until it is too late, or disruption suddenly occurs. When it does, if you are not prepared and able to respond properly the damage to your organization can be huge - you can lose your competitiveness, profit margins or overall business.

Thus, while waste is bad and we all want organizations to be lean, make sure that you and your people aren't pushed to the point they are never lifting their heads from the hamster wheel to look at the environment around them and aren't so tired they can't respond if the unexpected occurs. The damage that will result if they are will way exceed the benefits you thought you were realizing by keeping costs low. You definitely don't want to let the competition or environment hit you in the face.

Copyright 2013 Marc Borrelli

Thursday, April 18, 2013

Excel Users Beware - The Excel Mistake Heard Around the World

The Excel Mistake Heard Around the World

Research done by two Harvard economists, Ken Rogoff and Carmen Reinhart, found that when a country owes more than 90 percent of their GDP, it slides into recession. This research has been used around the world to justify austerity and the growing concerns of the size of government debt. The pair met with 40 senators in 2011 and "they told them, you need to act now and that we can't afford to spend more money to stimulate the economy." Also reading research by the two Harvard economists were budget chairs from both parties, then Treasury Secretary Timothy Geithner, the Simpson-Bowles Commission and financial leaders in countries overseas. "When we were talking about the budget deficit and the debt in 2010, 2011 and 2012, everybody had this 90 percent threshold on their minds," says Tim Fernholz, a business reporter with Quartz

However, it Reinhart and Rogoff made a glaring mistake in the Microsoft Excel spreadsheet they used to calculate their averages. "They left off five countries. And that changed things pretty significantly," says Fernholz. Instead of a mild recession, carrying that much debt means a country is probably going to have mild growth -- slow, but growth all the same.

In their defense, Reinhart and Rogoff point to other studies that show high debt leads to slow growth. But Fernholz says "it's not clear if countries that are growing slowly have high debt or if high debt causes countries to grow slowly." The Reinhart-Rogoff research suggested causation instead of correlation.

While not wanting to get into a huge debate about country debt and growth models, this simple mistake shows that policy and direction can be potentially misguided or just wrong due. In my earlier blog CFOs Beware: Problems with Financial Modeling, I raise the issues of problems with Excel and how they could effect modeling and thus the expected results or strategies for a company. Excel is a wonderful tool, but must be used carefully. As I worked with companies I have noticed that many of the models are extremely complex but within that complexity there is an increased chance for error. Often many of these errors, like computer code are not realized for a long time as the models are complex and in 70%+ of the cases the error doesn't affect the outcome. However, in those cases where it does, when the error has been discovered the costs is huge.

If a company were to make a similar mistake to the one by Rogoff and Reinhart, it could launch a new product, discontinue one, implement a new pricing plan or build a new plant which was going to lose them money. It is so much easier to do either through a incorrectly used range as in the above case or some hard coded number within a formula. A good friend of mine told me that a Fortune 100 company he was working with had a $200MM hard coded number in an Excel model that no one noticed and as a result it was skewing their investment strategies.

If two Harvard professors and a Fortune 100 company are making serious mistakes like this, the odds that there are mistakes in your models are pretty high. Need to check them carefully. Good modeling and planning but be careful.

Copyright 2013 Marc Borrelli



Monday, February 25, 2013

Precision v. Accuracy: How about using a range?

The concept of precision verses accuracy was first brought home to me back in the depths of time while I doing Physics "A" Level in high school and calculating measurement errors in experiments. From this I learned that no matter how precise one's measurements were, there an inherent error in the tool which was used to measure the results. Taking into account that lack of precision provided more accurate results, which is what we sought.

When I got involved in finance during my time in business school, the measurement tool was currency, and so precision was deemed to be the smallest currency unit, i.e. a cent. This precision was encouraged by the wonderful computing power of Lotus 1-2-3 and then Excel which allowed you to do forecasts that were precise to the cent going out years based on a few assumptions. While the precision was there, accuracy was foregone as we built huge models on a few simplistic assumptions.

However, upon leaving business school and entering the real world my illusions were quickly dashed. Having been at work less than a week, I presented my boss with a 10 year forecasting model which showed profit and loss statements, balance sheets, cash flows statements and of course a discounted cash flow valuation. He looked at it and asked how confident I was in my analysis. As I defended it, he looked at me and asked in a sort of Baynesian way, "Would you bet your bonus on company making the revenue numbers you have for this year?" (we were a quarter of the way into the year). 

"No!" was my quick reply. 

"In that case, how can you defend ten years of numbers which all build off that initial number?" he asked. It hit me and that has lived with me ever since that we quickly get sucked into the precision of our models, but really the numbers are so inaccurate.

During my career, I have see precise projections for sales, projects, costs being bandied around in companies by everyone, including the CFO. Yet few, if any, would bet a modest amount, let alone their bonuses, on those numbers being the final results. Thus we end up with the corporate situation where everyone knows the numbers are wrong but cannot admit it.

However, when working with these same companies and trying to get them to accept the concept of ranges in forecasts and probability distributions, I am regarded as though I had just stated that the earth was flat and supported by elephants. One CFO of a public company looked at me with total distane and asked "Why would anyone ever need something like that?".

When I responded that I was seeking more accuracy, albeit with less precision, in financial projections it was obvious that had I reverted to speaking Fanagalo. Another CFO used precise numbers (down to the dollar when their revenue was in excess of $20 million, and none of their forecasts were ever correct but he could not accept that forecasting to the million was acceptable. I heard that their last results were a huge surprise given the forecasts; however given the forecasting process I was not surprised at all.

This trade off of precision in return for greater accuracy continually is rejected by many of the financial professionals that I meet. I have wondered if the cause could be the focus on precision encouraged by the accounting profession that make it hard for these professionals to let it go.

So going back to my boss' logic - if you would not bet on a single number being accurate, would you be prepared to bet on a range? For example, the forecast may say that next years' revenue will be $10 million, but when pushed no one will bet their bonus on it. So would you be willing to be that it will be between $9 and $11 million or $8 and $12 million? When you reach a range that you would be willing to bet on, then surely that is the range to use in the forecasts.

Using ranges like this and applying techniques like Monte Carlo simulations results in far great accuracy in forecasts and an understanding of the risk profile of the results, i.e. there is a 50% probability that revenue will between $9 million and $10 million or that profits will between $0 and $1 million. Furthermore one can see what items are key to the final results what is not. Thus company's can focus on those key items rather than getting distracted by the noise.

It is best to remember Nils Bohr's quote "Prediction is very difficult, especially if it's about the future." Therefore, to make the predictions more useful, it is best to forego precision in return for greater accuracy.

Copyright 2013 Marc A. Borrelli

Tuesday, February 12, 2013

What are you measuring and why?

In my discussions with many CEOs and CFOs it is always interesting to see what is measured and tracked. However, many times they are not measuring the right things. Here are five suggestions of what and howto measure.

1. Measure your mission / differentiation goals. 

In reading the goals or mission statements of many companies, often you will see "we provide superior service to our clients". This is a very worthwhile goal or aim; however, once I get involved with a company I notice that there is no metric of customer service and satisfaction that is tied into key metrics and that drive performance bonuses. Furthermore, those that are measured are often measured in isolation and are not tracked in blind tests against those the of competitors or potential customers that didn't choose the company's products or services. Whatever is claimed to be the company's differentiation and vision should be measured and tracked to ensure that is what is being delivered.

2. Make sure you measure your strategy expectations

If embarking on a new strategic initiative ensure that you know what your expectations from the strategy are and then develop the appropriate metrics to measure its performance. Again many companies embark on new strategies and the metric tracked is often the financial contribution. Tracking financial contribution is also a worthwhile aim; however, it is the result and cannot always tell you what is driving those results. I like to think of it as measuring Return on Equity, rather than doing it through the Du Pont analysis. While both give you the same result, the latter is much more informative as it breaks down the ROE return into different performance metrics allowing you to understand what is driving the ROE as well as do better industry comparisons. In addition, this analysis should be broken down more to look at the key drivers of revenue and expenses. As I have said on prior blogs, usually its a handful of items drive 90% of the returns so these are the one that need to be focused on, not all the noise around them.

3. Measure cash

Cash is king and all CFOs know this. However, I find that many CEOs and CFOs in small to midsized companies are not always sure of what revenue does to cash. A simple measure that I like to look at is what I call Cash generated for $1 of Revenue. The formula for this is:

Cash Generated/Revenue = Net Margin - (Net Working Capital / Revenue) + [(Depreciation + Amortization - Capital Expenditure) / Revenue]

A company that I was involved with was proud of their net margin but was always cash strapped. Applying the above formula I got:

C/R = 9.3% - 24.5% + 1.5% = -13.5%

Thus for every additional dollar of revenue, the company needed $0.135 of additional cash to fund the cash shortfall. Thus the company's strategy of aggressively growing sales could drive them into bankruptcy if they were unable to raise capital to fund this growth. Many companies have found success to be lethal and this was another example.

As I learned many years ago from a wise adviser - fix the pipe before forcing more product through it. The key in the above was to focus on the company's Net Working Capital and reduce it so that the company was generating cash for every dollar of additional revenue. Once that had been accomplished they could drive sales aggressively.

4. Tie compensation to variables that employees can influence and will continue to influence

During my career I have worked with a number of large and small companies and can say that often a large piece of the incentive compensation of many departments has been tied to things that they have no control over. Examples of this are:

a. Net contribution of the department

In firm  bonuses were tied to net contribution of the department to the corporate profits. While this makes sense at a high level, the issue faced was that 50% of the department's costs were allocated by corporate HQ over which the department had no control. Doing some research it was determined that if the department could operated on a true stand alone basis with no allocated costs, it would save 10% of its costs. Thus it was proposed setting up the division separately where they would have full control over their costs, but this was rejected on the basis that if they did that then the additional costs would have to born by other departments.

Tie your employees bonuses to their direct costs which they control and measure those! If the HQ is allocating central costs then senior management is in charge of those costs and they should be rewarded on control of those costs. To often bloated central costs are divided up between departments and no looks at them carefully because they are not measured in a meaningful way.

b. Tied to operational results which excluded the departments activities

In another firm I have experience with the M&A department's compensation was tied to corporate profitability; however, the M&A department is really a cost center and there is little it can do for the overall costs of the company. Better metrics would be to tie it to the value generated by the transactions it executed, the time and effectiveness of integration planning, minimizing the costs of third party professional in doing transactions etc. These are items it could control and employees would be more incentivized to meet their objectives. So the key is to develop the appropriate metrics to drive the results that are sought.

c. Sales compensation tied to a 10 year future income stream that is not guaranteed.

Finally, I have come across situations where the sales team is incentivized by the potential revenue they generate for the company. Again this would seem to be the right motivation. However, the salesmen were being paid the present value of a ten year contract and in no example did I ever see the projections for income do anything but go upwards in a linear fashion (unless it was a hockey stick!). However, looking back over the company's history this had never once been the case in a ten year contract - Yes Virginia business cycles are real. Finally, once the salesmen signed a client they had no incentive to ensure the client stayed with the company for the full 10 years or generated the potential income on which they had been compensated. When I discussed this with the finance department they were all aware of the issues but said that if they changed the compensation all the salesmen would leave. They were helpless. A worrying signal about the corporate culture!

5. General Statistics

This may be an odd heading but I see time and time again people using statistical tools without the full appreciation of them so here are two simple reminders. For example I see people doing lots of regression analysis in Excel to project some future cost or revenue item, but when I ask if the date sample is normally distributed I get blank stares - you cannot do regression analysis if its not!

a. Need sufficient data to draw conclusions

It is amazing how many projections or statistical inferences are developed off a few data samples. Just as a reminder if you have 100 samples the error bounds on the results are 10%, to get the error bounds down to 3% the sample size needs to be 1,000. Therefore, it is always worrying when a few samples, i.e. less than 50 have been used to generate some estimate and the estimate is given with definite precision from an Excel model. There are no ranges in the model, and it all falls back into the precision vs accuracy issue.

b. Correlation does not imply causality

This seemly obvious rule is one that it would appear no television forecast has ever been made aware of. Listening to statements like "the team that is leading at the end of the 1st quarter always wins" makes me want to cry. But I see the same logic applied in corporate modeling and measurements where the equivalent of "the coin has been tails the last four throws so it will be again" is expressed with confidence. There is little question of what drives what or why the results are correlated. Remember you derive a formula to match any set of data points but it may be meaningless.

c. Measure the important stuff

As I mentioned above and as represented in the Pareto Principle, 20% of the variables drive 80% of the results. Thus focus on those items that drive the results and spend time and effort to measure and understand them correctly. The rest are not as important and can easily estimated as they will not affect the ultimate outcome significantly.

Wednesday, January 30, 2013

CFOs Beware: Problems with Financial Modeling

Through my work I have dealt with thousands of Excel, and for those that remember Lotus, financial models and I have to say that most of them are bad. I would like to summarize five of my least favorite things about the "bad" models I have had the unfortunate experience to deal with during my career. All of these issues, except the last one, are sufficient enough for me to walk away from the work or opportunity as they indicate that I am likely to find more problems in the finance area or business.

  1. Excessive precision. When I see models that have numbers in the millions and show accuracy to dollar, or even worse the cent, red flags fly. That much precision is a distraction and is usually wrong, especially if it is a forecasting model. In the words of Niels Bohr, "Prediction is very difficult, especially about the future." Thus models that predict amounts to the dollar a year away are wrong. Ask yourself, what level of accuracy is needed. If you are dealing in tens of millions and you show numbers to the thousand, the error level is 0.01% which is more than enough precision. Another test is would you be willing to bet on the outcome being right to that level of precision, and if not ask why are you showing it. Remember the old adage - "I would rather be 90% right and imprecise than precise and 100% wrong.
  2. Hard coded numbers. Models that have hard coded numbers in them also raise red flags. Users forget they are there and they remain forever with no rhyme or reason leading to bad results. Also if things change it is hard to find them and change them in all the cells that need changing.  Finally, requiring hard coded numbers to change a model to get it to produce correct results, could mean the model is fatally flawed in design and operation - time to start again.
  3. No tracking of results. Recently met a firm that had a model it had been using for all its forecasting for years. I enquired as to how accurate it was and the answer was that the last month had been a huge surprise, but no one had ever tracked its results against actual. If the model is not measured, its effectiveness is not know or cannot be fixed. Thus one could be relying on something totally wrong for years and not realize it. No model is perfect and they are like an iterative process, use them, measure the results and then adjust them to get to improve the results.
  4. Understand the logic of the model. Understand what the model is trying to accomplish. Often it is good to diagram out how all the parts are going to fit together and where the different parts will reside in the model. In addition think through all the parts carefully about how they work and what they do. It is my experience that usually 6 - 10 items contribute to the majority of the values and so they need the most precision, the rest will not change things much and we don't need to focus on those as much. In addition, beware of some important items, i.e. exchange rates. A model I was received recently had no exchange rate assumptions even through the company had significant European operations - this oversite would lead to incorrect forecasting. Finally remember all the parts - again the same complex financial model for business forecasting that I mentioned above showed P&L, Balance Sheet and Cash Flow statements as well as many other iterations of the data; however, the model didn't distinguish between book and tax depreciation which would lead to incorrect cash flow statements as well as errors elsewhere. 
  5. Layout. A model should be like a book or an essay - an introduction - the characters - the plot - the conclusion. Many I have seen have everything mixed up and you cannot follow the logic or flow which makes it hard to read and work with. Make the model easy for the user to follow and read. Thus, I would recommend:
    • Put in a tab which explains what it does and describes what is on each tab as well as the color coding if you are using it.
    • Use the cell indents for indentation, not another column
    • Use colors - it makes it very easy to see what are inputs, assumptions, outputs etc. If all input cells are yellow then the user can easily know what to change
    • Use lists to control inputs - prevents mistakes accidentally happening.
    • Spell check - it is built in so use it.
    • Make it clean and easy to read.
    • More tabs with a purpose are better than one huge tab that is difficult to navigate around.
    • Break tabs down into: Assumptions, Working, Results. Makes it much easier to follow.
    • All assumptions should feed into the appropriate parts of the model - just showing them is useless. In addition, remove cells that contain assumptions that don't feed into anything or do calculations for no specific purpose.
    • Put in check boxes - if you are building a forecasting model put in a line showing that the balance sheet balances. Thus if it doesn't you can easily see it rather than suddenly realize it when it is too late.
I hope that you find these useful. Good luck forecasting.

Copyright 2013 Marc Borrelli

Friday, January 6, 2012

Lessons I Learned from Squash that Apply to Business


First, I would like to wish everyone a Happy New Year and all the best for 2012.

The last piece in my series “Lessons I Learned from Sports that Apply to Business” covers a game that I love and only wish my ability was matched by my passion – Squash.  I have played the game for longer than I care to admit, but fortunately my understanding of the game has improved with time. The key points from squash that apply to business are, in my opinion are: (i) dominate the “T”; (ii) keep the other person on the defensive; (iii) not every stroke is a winning one; and (iv) when stuck in a war of attrition, change the game!

Dominating the “T”

In squash, the “T” is an intersection of lines near the center of the court where the player is in the best position to retrieve the opponent’s next shot. Skilled players will return a shot and then move back to the “T” before playing their next shot. From this position the player can quickly access any part of the court to retrieve the opponent’s next shot with a minimum of movement.

However, in order to return to the “T” in a timely fashion, the player needs to measure the way they approach the ball for the shot, keeping low and flexible, and maintain their center of gravity over their legs. If they throw themselves at the ball in order to reach it, they could end up being in a position which my coach fondly referred to a as being in “extremiss”. Basically the player has committed so much to the shot that they cannot easily return to the “T” as their bodies are not in a neutral position from which they can change direction. In such a position and unable to return to the “T”, they allow their opponent to win the point by placing the ball where they cannot get to it.

In business, I believe the same is true. The future is uncertain and the past is not always a guide to the future. Over the last few years we have experienced “Black Swan” events and felt the impact of “fat tails”. Corporate strategy is about managing the uncertainty by creating a portfolio of the necessary strategic and growth options which allow the company to respond to a changing environment – in effect returning to the “T”. If a company commits to a strategy which does not allow it to deal with uncertainty, it is effectively in “extremiss” and is so cannot recover to the corporate “T”. However, this is not to say that the company, it management and employees are not committed to the strategy chosen, just that if the environment changes such that the strategy is not working, the company can quickly adjust.

 Not Every Shot is a Winning Shot

In squash, as the players get better the rallies get longer and the game becomes a war of attrition. Thus, the aim of the game is keep the other player on the defensive until you are in a position to hit a winning shot.  By hitting the ball deep and in the corners it reduces the other player’s ability to hit an attacking shot. In that regard, many of the shots that are hit, are not winning shots, but designed to put the other player on the defensive and move them in the back of the court and so that you can set up an attacking shot.

In business many see a winning product and think that is what destroyed the competition and put the company on top. However, while I think that a great product or strategy helps – and in the case of a disruptive technology maybe essential, most of the time, the key is to be continually pushing your competition into a defensive position from which they cannot attack you and so when you launch the winning product, the competition are effectively neutralized and not able to muster an adequate response. Apple is good example as it continues to release of new products or significant updates which keeps its competitors on the defensive and continually playing “catch up”. This enables Apple to extend its market lead and redefine the market.

Often it is the follow up to the Winning Shot that wins the Point

As was mentioned above, as the players ability improves the game becomes one of attrition and there are not many opportunities for an “ace” or a “winning shot” that your opponent cannot reach. In reaching the ball to return the winning shot, often puts your opponent in a position where they are no longer balanced and thus they are unable to return to the “T” prepared for your next shot, and it is that shot that wins the point.

In business while most planning is done on a ceteris paribus basis, the launch of a new product or strategy nearly always elicits a response for the competition – following Newton’s third law “for every action there is an opposite and equal reaction.”  However, if in responding to your strategy or new product, the competition has put themselves in a position where they are unable to effectively respond to your next move, you can take a market leadership position or redefine the market.

Many studies have been done that show that those companies that emerge as market leaders during periods of market turbulence and recession often hold that position for a long time.  This is due to the fact that during market recessions and turbulence, resources – both human and financial - are stretched and the ability of companies to respond effectively is compromised. So if a company launches a winning product or redefines the market redefined during such a period, the competition cannot respond adequately and the company can take a market leadership position. An example of this was the emergence of Amazon as the market leader in online shopping following the 2000/2001 recession.  As the economy returns to a period of stability, human and financial capital is available and so the company responds more effectively and the ability to gain that market leadership is more limited.

When stuck in a war of attrition, change the game

In squash, if you get into a war of attrition unless you are far fitter than your opponent and don’t mind, it is best to change the game so that you retake the advantage. Changing the game is done by (i) changing the tempo of play; (ii) changing the height of the ball; or (iii) being unpredictable. In business, it is the same, if you and your competition are fighting but no one is winning, you have to change the game. This is either by:

·         change the tempo – speed to market of new products, reaction to the competition or the introduction of new products. By changing the speed of these, you can throw off the competition and move yourself into a more competitive position. Not all of these have to be done faster, by slowing down some of these, you can prepare yourself better so that the launch of the product or the response is better planned and executed.

·         change the height - redefine the market and what are the key selling points of the product. At times like this look at the market and determine if you can redefine it such that you are selling on a different basis. Examples are: the Apple Ipod changing the market from a music player to a music store; and Valtra, a Finnish tractor company, that became the Dell of the tractor industry – they would build it to the client’s specifications, paint any name on it, and clients were invited to watch it being assembled. This changes the base of competition.

·         be unpredictable! More risky, but has been said in my prior blogs, strategies that can grow a company have the same characteristics of those that cause the company to fail. You cannot succeed by being safe.

Copyright 2011 Marc Borrelli

Tuesday, November 8, 2011

Lessons I Learned from Snow Skiing that Apply to Business


I have loved skiing ever since I first started 40 years ago. When I first started I thought the aim was to go straight down the mountain as fast as you could; however, a broken leg soon cured that misconception. Still today I see many people bragging about how they skied down this difficult run or the other, but having seen them on the slopes I realize that they are getting down with little style or ability, and gravity is the main contributor. While they have survived, the chance of doing this repeatedly is small. In business as in skiing, the key is to be able to do the successful things repeatedly.

Continuously adjust to changing conditions

Looking at great skiers, they move effortlessly down the mountain. All you see is the fluidity of their movement and their rhythm. What you never notice is the changing slope of the mountain and changing snow. When watching lesser skiers, you can tell when the conditions change – in the moguls, their rhythm abandons them and on ice they flail around. Thus the differentiating factor better a good skier and an average skier, in my opinion, is the ability to adjust continuously to the changing conditions below your feet.
In the corporate world those companies that can maintain the company’s performance through the continuous changing and challenging business and economic conditions are the great ones. They appear to make it effortless in their performance, but it is not, it requires great skill and the ability to anticipate and react to changing conditions. Coca Cola, well known as the largest provider of a number of soft drinks and beverages, manages to maintain its market leadership in Japan where there are over 7,000 different soft drinks and over 1,000 new products are launched every year. Coca Cola maintains that leadership by continuously introducing new products and adjusting to the changing conditions and tastes of it consumers.

Upper body is still, the skier looks ahead and the legs adjust and absorb.

Watch skiers as they ski the moguls, they are looking 2 to 3 turns ahead (remember where your eyes go your body follows) down the mountain. Their upper bodies are relatively still, while their legs are moving like pistons, absorbing and extending through the moguls as they guide their skies.
To me, the upper body is the strategy of the company, still focused ahead on the goals and plotting the best course ahead to achieve them. The legs are corporate tactics that are required by the environment to realize the strategy. Like the business environment, the mountain is never constant; success requires continually adjusting to the changing conditions by changing and adjusting tactics to reach the corporate strategic goals.
When skiing moguls, if you sit back on your skis, you lose the ability to steer the skis and so lose control and will crash. Often the solutions when you do start to sit back has been described as effectively throwing your body down the mountain so that your center of gravity will pass your feet and you can regain control of the skis and steer them. Companies often “sit back” and then are in trouble as the industry changes and they have no ability to change direction with it. An example of this, I would describe as Apple prior to Steve Job’s return. The company was sitting back not controlling its direction in the industry. To save it, it had to throw itself ahead and gain control of its direction in the industry.

“If there is no snow on your ski jacket you are not improving”

Phil Maher, the great US skier once told me this, and I have always appreciated it. What is meant by this statement is:

  • If you don’t have snow on your ski jacket you haven’t fallen.
  • If you haven’t fallen you are not pushing yourself outside your comfort zone; and
  •  If you don’t push yourself outside your comfort zone you are not growing.


The same is true of companies, if you don’t take risks you cannot succeed. Many writers have covered the thesis that the opposite of success is not failure, but not succeeding. Strategies that make companies successful are the same strategies that make them failures it just depends on how the future unfolds (See “The Strategy Paradox” by Michael E. Raynor). The tradeoff is that most strategies are built on specific beliefs about an unpredictable future, but current strategic approaches force leaders to commit to an inflexible strategy regardless of how the future might unfold. Thus success or failure is often up to chance. To be successful you have to commit to a strategy that has risk, but at the same time be flexible and adaptable. Regardless, there are times when the company will “fall”. If the company cannot fall, it must play it safe so as not to fail; however, nor can it cannot succeed, it just exists in constant state of mediocrity leading to a slow demise.

Many companies and management teams play it safe as they will still receive their compensation but not face risk. A recent McKinsey article suggested that companies should innovate more but behavioral bias is stopping them and they are too risk adverse (http://bit.ly/oC5XyU). Taking risk implies there will be failure, but often that growth and sometimes the failure can take the company in a new direction which was not anticipated leading to greater success. However, failing to take on risk stops the organization and its management growing. When they stop growing they lose the ability to adjust to change effectively and the ability to take risk, as behavior, is weaned out of the company. At time like that many companies try to buy their way out of trouble, acquiring new technologies and clients at excessive multiples which often just delays the death spiral. That is because the risk taking culture and learning through growth has gone, and so while the company adds products and clients, the underlying behavior doesn’t change so the decline continues.

Copyright 2011 Marc Borrelli