Why most sales forecasts suck…and how Monte Carlo simulations can make them better

Sales forecasts don’t suck because they’re wrong.  They suck because they try to be too right. They create an impossible illusion of precision that ultimately does a disservice to managers who need accurate forecasts to assist with our planning. Even meteorologists — who are scientists with tons of historical data, incredibly high powered computers and highly sophisticated statistical models — can’t forecast with the precision we retailers attempt to forecast. And we don’t have nearly the data, the tools or the models meteorologists have.

Luckily, there’s a better way. Monte Carlo simulations run in Excel can transform our limited data sets into statistically valid probability models that give us a much more accurate view into the future. And I’ve created a model you can download and use for yourself.

There are literally millions of variables involved in our weekly sales, and we clearly can’t manage them all. We focus on the few significant variables we can affect as if they are 100% responsible for sales, but they’re not and they are also not 100% reliable.

Monte Carlo simulations can help us emulate real world combinations of variables, and they can give us reliable probabilities of the results of combinations.

But first, I think it’s helpful to provide some background on our current processes…

We love our numbers, but we often forget some of the intricacies about numbers and statistics that we learned along the way. Most of us grew up not believing a poll of 3,000 people could predict a presidential election. After all, the pollsters didn’t call us. How could the opinions of 3,000 people predict the opinions of 300 million people?

But then we took our first statistics classes. We learned all the intricacies of statistics. We learned about the importance of properly generated and significantly sized random samples. We learned about standard deviations and margins of errors and confidence intervals. And we believed.

As time passed, we moved on from our statistics classes and got into business. Eventually, we started to forget a lot about properly selected samples, standard deviations and such and we just remembered that you can believe the numbers.

But we can’t just believe any old number.

All those intricacies matter. Sample size matters a lot, for example. Basing forecasts, as we often do, on limited sets of data can lead to inaccurate forecasts.

Here’s a simplified explanation of how most retailers that I know develop sales forecasts:

1. Start with base sales from last year for the the same time period you’re forecasting (separating out promotion driven sales)
2. Apply the current sales trend (which is maybe determined by an average of the previous 10 week comps). This method may vary from retailer to retailer, but this is the general principle.
3. Look at previous iterations of the promotions being planned for this time period. Determine the incremental revenue produced by those promotions (potentially through comparisons to control groups). Average of the incremental results of previous iterations of the promotion, and add that average to the amount determined in steps 1 and 2.
4. Voilà! This is the sales forecast.

Of course, this number is impossibly precise and the analysts who generate it usually know that. However, those on the receiving end tend to assume it is absolutely accurate and the probability of hitting the forecast is close to 100% — a phenomenon I discussed previously when comparing sales forecasts to baby due dates.

As most of us know from experience, actually hitting the specific forecast almost never happens.

We need accuracy in our forecasts so that we can make good decisions, but unjustified precision is not accuracy. It would be far more accurate to forecast a range of sales with accompanying probabilities. And that’s where the Monte Carlo simulation comes in.

Monte Carlo simulations

Several excellent books I read in the past year (The Drunkard’s Walk, Fooled by Randomness, Flaw of Averages, and Why Can’t You Just Give Me a Number?) all promoted the wonders of Monte Carlo simulations (and Sam Savage of Flaw of Averages even has a cool Excel add-in). As I read about them, I couldn’t help but think they could solve some of the problems we retailers face with sales forecasts (and ROI calculations, too, but that’s a future post). So I finally decided to try to build one myself. I found an excellent free tutorial online and got started. The results are a file you can download and try for yourself.

A Monte Carlo simulation might be most easily explained as a “what if” model and sensitivity analysis on steroids. Basically, the model allows us to feed in a limited set of variables about which we have some general probability estimates and then, based on those inputs, generate a statistically valid set of data we can use to run probability calculations for a variety of possible scenarios.

It turns out to be a lot easier than it sounds, and this is all illustrated in the example file.

The results are really what matters. Rather than producing a single number, we get probabilities for different potential sales that we can use to more accurately plan our promotions and our operations. For example, we might see that our base business has about a 75% chance of being negative, so we might want to amp up our promotions for the week in order have a better chance of meeting our growth targets.  Similarly, rather than reflexively “anniversaring” promotions, we can easily model the incremental probabilities of different promotions to maximize both sales and profits over time.

The model allows for easily comparing and contrasting the probabilities of multiple possible options. We can use what are called probability weighted “expected values” to find our best options. Basically, rather than straight averages that can be misleading, expected values are averages that are weighted based on the probability of each potential result.

Of course, probabilities and ranges aren’t as comfortable to us as specific numbers, and using them really requires a shift in mindset. But accepting that the future is uncertain and planning based on the probabilities of potential results puts us in the best possible position to maximize those results. Understanding the range of possible results allows for better and smarter planning. Sometimes, the results will go against the probabilities, but consistently making decisions based on probabilities will ultimately earn the best results over time.

One of management’s biggest roles is to guide our businesses through uncertain futures. As managers and executives, we make the decisions that determine the directions of our companies. Let’s ensure we’re making our decisions based on the best and most accurate information — even if it’s not the simplest information.

What do you think? What issues have you seen with sales forecasts? Have you tried my example? How did it work for you?

“Obscure and pregnant with conflicting meanings”

We’ve all heard the cliché “hindsight is 20/20” a thousand times. And it’s pretty much true. It’s a lot easier to figure out the path to a particular event when you know the final outcome. But if “what happened” is something bad, determining the reason after the fact doesn’t change the negative event.

How can we do a better job finding those problems in advance of our next new strategy implementation, site redesign, store remodel or other big effort?

It’s worth digging a little deeper to better understand why our hindsight is so perceptive. One of the most famous cases of 20/20 hindsight comes from the investigation into the attacks on Pearl Harbor (although, we could also argue the investigation into 9/11 and the more recent Fort Hood shootings have many similarities). In her book Pearl Harbor: Warning and Decision, noted military intelligence historian Roberta Wohlstetter wrote “it is much easier after the event to sort the relevant from the irrelevant signals. After the event, of course, a signal is always crystal clear; we can now see what disaster it was signaling since the disaster has occurred. But before the event it is obscure and pregnant with conflicting meanings.”

Of course, Pearl Harbor was an unexpected disaster that seemingly came out of nowhere. While we have those occasionally in business, more often than not our “disasters” come from strategies, redesigns or promotions that did not perform as expected. And those expectations can also lead to our blindness.

Whenever we’re implementing some new and exciting strategy, we tend to be very optimistic about the results. We’re convinced these new strategies are going to provide positive returns or we wouldn’t be implementing them. That optimism can lead to the same sort of crystal clear signal Wohlstetter referenced, but in the opposite direction; i.e. we tend to only see how everything we’re doing will lead to greatness and can easily overlook variables that have potential to lead to negative outcomes.

So, what do we do about it?

It seems some of the most common solutions today involve pulling together a committee to review what went wrong and putting together processes to prevent those specific problems in the future. These new processes don’t prevent all potential problems in the future, but with any luck they’ll prevent us from repeating the same mistakes.

But all of that happens after the fact.

There’s got to be a better way. My problem with the “committee and new process” approach is there’s a tendency to introduce lots of new and –all too often — needless bureaucracy. Inefficiencies ensue without greatly decreasing the probability of problem-free future efforts.

A technique I’ve found effective invokes much of the clarity of hindsight by drawing on the power of imagination.

During the ROI process for the strategy or project, we’ve already imagined the positive outcome. So before we wrap up planning, let’s also imagine a couple horrific scenarios. For example, imagine that four or five months after a site redesign, sales are down 50% and customer satisfaction has tanked. What happened? Now let’s assemble the same type of committee we would in that scenario and pour over the plan to find the causes of our imagined disaster.

Some might say this technique is really just standard contingency planning, but I find some pretty big differences. Contingency planning tends to look at the current plan to identify execution risks. It doesn’t often uncover key strategic or design problems.

The Scenario Imagination technique provides us with a different sort of lens that taps into our hindsight abilities to separate the signal from the noise.

We certainly won’t find every potential problem, but every problem we mitigate increases our probability of success and reduces our risk. And if we can reduce a lot of risk without strangling ourselves in bureaucracy, we’ll likely lower costs, increase efficiencies, and increase profits. I like the sound of that.

What do you think? Have you run into these types of issues? Do you think this technique would work for you? Do you have any techniques you would like to share?

Photo credit: me’nthedogs

“If it ain’t broke, you ain’t looking hard enough”

The poor economy has done nothing to lower customer expectations of online retailers, and recent mixed results data from ComScore and ForeSee Results indicate that retailers who continue to improve their customer experiences are pulling away from their competitors in both sales and customer satisfaction.

ComScore reports online retail up 4% for the holiday season. While an increase is always nice, this is a much lower growth rate than online retail has seen in the past. And last year’s comparison base was far from stellar. ForeSee Results shows a significant drop in customer satisfaction year over year. Since satisfaction is predictive of future financial results, a drop is concerning.

But still, I wondered how sales could be up at all if satisfaction was so far down.

A deeper look at the ComScore data shows the Top 25 retailers growing 13% while “Small and Mid Tail” retailers are declining 10%. Satisfaction scores are also split, but the differences we’re seeing seem to be more based on those retailers who are continually improving their sites versus those whose cost containment measures have slowed or stopped improvements. It appears that the retailers who closely measure the effectiveness of their sites from their customers’ perspectives and continuously improve their customers’ experiences are the retailers with increasing customer satisfaction scores. Those retailers who didn’t improve customer experience this year are suffering declining satisfaction scores. Many of those in the Top 25 are the retailers who have continued to enhance their customer experiences. Those enhancements are not only helping them to increase their sales, but because of the high visibility and usage of those tops sites, they’re also raising consumer expectations of all sites.

Customer satisfaction can be best defined as the degree to which a customer’s actual experience meets his or her expectations. Therefore, rising expectations can depress satisfaction scores if customer experience improvements don’t keep pace.

In the rapidly changing world of online retail, stopping or delaying improvements is like treading water in a swimming race. While you may temporarily save some energy, you will fall hopelessly behind and your only hope of catching up is spending a lot more energy than you likely saved treading water

Growing online retail businesses realize and fully embrace the need for continuous improvements, and they also realize that online retail in general is far from producing the level of customer experience truly necessary to provide excellent self-service shopping experiences. I recently heard Robin Terrell, Managing Director of John Lewis Direct in the UK (and Amazon alum), say “If it ain’t broke, you ain’t looking hard enough” in a talk about the need to improve customer experience. It’s a brilliant statement, and I totally agree with what he was saying.

So, “improving customer experience” is a huge and vague statement. Where do we start?

1. Recognize that it’s broke and you ain’t looking hard enough
   We’re still in our infancy in online retail, and we’ve got a long way to go. We too often try to increase our sales by generating more traffic and don’t spend enough time converting the traffic we’re already got. Often, the obstacles to conversion are not the big, shiny, whiz bang functionality; they’re lots of little things that add up to big problems. Those problems are hard to see without a concerted effort, as I discussed in more detail in my Tree Stump Theory post and other posts on conversion.
2. Truly learn how effective your site is from your customers’ perspective
   We can all identify lots of improvements we’d like to see on our sites, but it’s the improvements our customers most need that will drive our best growth. So understanding where we are and aren’t effective from our customers’ perspectives is critically important, but difficult.Focus groups and usability labs can be very helpful, but they can’t be our first or only methodology because it’s not possible to project learnings from a small group of people onto our entire population of customers.

   First, we need to quantitatively understand our effectiveness in the eyes of our total population, and that requires a statistically solid customer polling and analysis capability. Blatant and shameless plug alert: I’ve had great success using ForeSee Results in the past for exactly this purpose. Once we understand problem areas at a macro level, we can add a lot of color by interacting directly with customers in focus groups and usability labs. More details on this process can be found in my post entitled “Is elitism the source of poor usability?”

3. Consider getting some help from usability professionals
   Usability audits are different from usability labs. Usability auditors are professionally trained to understand how people interact with websites. Many of them have degrees in Human-Computer Interaction, a field that truly seeks to understand how people interact with software. These types of people can really help to identify problems with our user interfaces that untrained eyes have trouble seeing but which regularly obstruct customers from accomplishing their tasks.
4. Put in place a process to continuously improve
   This is really about budgetary and project management mindset. We must just accept the fact that we can’t tread water in a never-ending swimming race, and our only chance of competing is to keep swimming. We have to build our staffs, our budgets and our processes with the recognition that competing in the marketplace means continuously improving our customer experiences. Which leads to …
5. Wash, rinse, repeat
   Since the leaders in the marketplace are running this same cycle, we cannot rest. We must continue to recognize our sites are broken, continue to measure our effectiveness from our customers’ perspectives, find problems, fix them and begin again.

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We’ve got a lot of data that shows that retailers who best satisfy their customers generate the best financial results. I suppose that statement doesn’t sound like rocket science. But understanding that satisfaction has a direct relation to expectations and that our customers’ expectations can change independent of what we do on our own site is important. The leaders are continuously improving their sites, and they’re improvements are raising our customers’ expectations. We’ve all got to swim harder to keep pace.

What do you think? What’s your view on the marketplace? How have you see customer satisfaction affect your business?

The Hidden Cost of Change

Imagine a scenario where you and your business competitors all join in a pact to share your largest revenue sources, pool most of your marketing efforts and limit your respective payrolls to the exact same amount. You all sell the same product. Would you expect each of your companies to perform about equally well?

According to this article, the NFL expected such an arrangement to produce parity — but it doesn’t seem to be panning out. A few teams stand out as being consistently great over time and a few others (including my beloved Cleveland Browns) have been consistently terrible.

Are these success and failure stories the result of random luck, or are there some business lessons to be learned?

I’m not sure there’s enough data to completely rule out streaks of good and bad luck, but some of the analysts quoted in the article offered some reasoning that at least got me thinking about business lessons.

Former Colts coach Tony Dungy went to the playoffs in each of his seven seasons in Indianapolis and won the Super Bowl after the 2006 season. The key to winning, he says, is “having everyone on the same page and going in the same direction. The more stability you can get, that’s how you’re going to win.”

“I think one of the biggest reasons why teams aren’t getting better is instability,” says former Bills coach and general manager Marv Levy, who coached the team to four consecutive AFC titles from 1990 to 1993. “It’s always, ‘Let’s change, let’s change. This constant ‘We have to shake it up’ is causing some of this (disparity).”

Both quotes struck me as pretty meaningful in the business world. In my experience, big changes are disruptive and expensive — both in real terms and in opportunity costs.

For the record, I am definitely not anti-change. In fact, I love change and the eternal optimist in me is prone to almost always seeing the greener grass on the other side. But it’s helpful for me to remember that change does have its hidden costs to be considered.

Real costs
Large scale changes, be they new strategic plans, remodels, site redesigns or something similar, have real costs in their preparation and capital expenses. Since those are more obvious, I’ll move on to…

Opportunity costs
Implementing new change is hard work that takes a lot of time and effort. Diverting attention from current efforts creates opportunity costs and can cause a business to fall behind and lose market share during the buildup. Also, in my experience, big changes like store remodels and site redesigns tend to cause temporary step-backs in business and customer satisfaction (which can have longer term effects) due to the “where’s my stuff” syndrome.

Talent costs
Big changes like strategic shifts due to leadership changes tend to have human costs. For example, I’ve found over the years that any “A” player can become a “C” player if put into the wrong situation. Replacing team members is expensive and can lead to some of the opportunity costs listed above.

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Again, I’m an certainly not arguing against change. But in my experience too frequent wholesale changes can generate costs that outweigh the benefits, which is what the NFL coaches quoted above seem to be saying.

At a recent speaking engagement, someone asked me if it’s better to implement occasional site redesigns or take a more continuous improvement approach. I’ve found the continuous improvement approach to be more effective because it’s less disruptive to employees and customers alike. But that doesn’t mean revolutionary change isn’t necessary at times. After all, defending the status quo kills companies. We just have to be careful how often we revolt and make sure revolution is truly the smartest long term move.

But, hey, I’m still thinking through this issue. I would certainly benefit from your thoughts and perspectives. What do you think?

Best Business Books of the Year

With the holiday season upon us, I thought I would write about my favorite business books of the year to provide some gift giving ideas for you and your teams. Here, in no particular order, are my favorites among the books I read this year. (Note: These books were not all published this year, but since I read them this year I’m including them in my list.)

Six Pixels of Separation: Everyone is Connected. Connect Your Business to Everyone.
by Mitch Joel

Six Pixels of Separation begins as a primer for any business leader with limited knowledge of the Internet’s capabilities and quickly turns into an indispensable set of guidelines and advice for any business person who plans to make use of the web (which should be any business person). Mitch Joel offers excellent insight and plenty of simple, direct, digestible advice. This is a must read.

The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty
by Sam L. Savage

Every business person should read this book. We are so often looking for precise numbers when precise numbers are unrealistic. The reality is, we would actually be much more accurate to use probabilities and ranges when referencing uncertain number such as sales forecasts or project timelines. Savage takes us through the dangers of using averages to describe distributions and offers solid solutions that can be used to better manage our business.
Preview Flaw of Averages

Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets
by Nassim Nicholas Taleb

This book made me think more than any book in recent memory. That may be partly because it’s pretty dense and I had to read it more slowly than I normally read. However, I’ll give a lot more credit to the fact that Taleb’s makes some very interesting points about the amount of randomness in our lives and how that randomness is all too often mistaken for something more substantive.
Preview Fooled by Randomness

How We Decide
by Jonah Lehrer
I loved this book. Jonah Lehrer takes us through some fairly common behavior economics principles and experiments, but the very interesting twist he takes is to explain the brain mechanics that drive our thinking and decisions. He really uncovers why we’re “predictably irrational” and provides great insight into how we make decisions and how we can use that knowledge to improve our decision making.

The Drunkard’s Walk: How Randomness Rules Our Lives
by Leonard Mlodinow

I’m on a randomness kick lately, and this is the book that got me started on it. Mlodinow does a nice job of illustrating some of the finer statistical points in a pretty accessible manner. While this book isn’t as deep at the book I’m currently reading, “Fooled by Randomness,” it’s definitely an easier read and does a nice job of covering the basics.
Preview The Drunkard’s Walk

Sway: The Irresistible Pull of Irrational Behavior
by Ori Brafman, Rom Brafman

Another one of the behavior economics books I so love. This one has some pretty interesting stories and anecdotes, and its insights benefit from one of the writers being a psychologist and the other a businessman.
Preview Sway

More Than a Motorcycle: The Leadership Journey at Harley-Davidson
By Rich Teerlink and Lee Ozley

This is a very interesting book about culture change at Harley-Davidson during the ’90s written by the CEO and lead consultant who initiated the change. It can be a bit dry at times, but the details behind the thinking and the execution are excellent. I learned a lot by reading it.
Preview More than a Motorcycle

And here are some great books that I re-read this year:

The OPEN Brand: When Push Comes to Pull in a Web-Made World
by Kelly Mooney, Nita Rollins
The world is changing rapidly, and those who fail to realize it will be left in the dust. However, those who open their brand and see the value of allowing their best customers to participate in the brand will not only reap the benefits of those customers ideas, but they will also benefit from those customers becoming the largest and more credible Marketing department a company could have. Kelly Mooney and Nita Rollins explore these themes in an extremely insightful book that comes with lots of examples that help the reader visualize how these ideas could apply to his or her own business. The writing style and formatting is fun and extremely easy to read. This is a great handbook for any marketer in the 21st century.

Moneyball: The Art of Winning an Unfair Game
by Michael Lewis

While this is ostensibly a baseball book about the success of Oakland A’s GM Billy Beane, I actually found this to be an excellent business book. Michael Lewis tells the story of Beane defying the conventional wisdom of longtime baseball scouts about what good baseball players look like. Rather than trust scouts who literally would determine a baseball player’s prospects by how he physically looked, Beane went to the data as a disciple of Bill James’ Sabermetrics theories. Lewis describes how James took a new look at traditional baseball statistics and created new statistics that were actually more causally related to winning games. By following the James’ approach, Beane was able to put together consistently winning teams while working with one of the lowest payrolls in the Major Leagues. How can the same principles of trusting data over tradition and “gut” play in the business world? That is a thought I constantly ponder thanks to reading this book.
Preview Moneyball

The Culture Code: An Ingenious Way to Understand Why People Around the World Live and Buy as They Do
by Clotaire Rapaille

I picked this book up on a whim one day because the title was interesting. I was quickly engrossed by reading the story in the introduction of Clotaire Rapaille’s work with Chrysler on Jeep Wrangler. He describes the “code” word for Jeep in America is HORSE and advises executives to design round headlights instead of square headlights because horses have round eyes. They think he’s nuts, of course, but when it turns out round headlights are cheaper they go with them — and they’re a hit. They also then position the Wrangler as a “horse” in their ads and have great success. Rapaille goes on to describe what he means by “culture code” and details some of the hidden cultural patterns that affect most all of us. Some samples of other codes within the book are:
- The American Culture Code for love is FALSE EXPECTATION
- The female code for sex is VIOLENCE (Whoa! You’ve got to read the book to understand)
- The code for hospital in America is PROCESSING PLANT

There are tons more of these interesting observations embedded in short, easy-to-read chapters. Whether or not you buy into everything he says, it’s very interesting to see how he developed each code and certainly will expand your understanding of how and why people behave as they do under the powerful forces of culture
Preview The Culture Code

Predictably Irrational: The Hidden Forces That Shape Our Decisions
by Dan Ariely

This is the book that first turned me on to the fascinating world of behavioral economics. Ariely does an excellent job of explaining many of the core principles of behavioral economics with stories and experiments. Every retailer should read this book to better understand how people (customers) think and behave. It will absolutely open your eyes.

Those are some of my favorites. I’m always looking for a new read. What books fired you up this year?