Category Archives: Revenue Risk Management

Five Incredibly Exciting Ideas for Managing Revenue Risks

We’ve all endured small talk at networking events. “. . . and last year, when my daughter and I stayed with one of my sorority sisters, she discovered this weird mole on her leg, and . . .” Your fascination maxes out in the first five seconds as your mind wanders to other things, like whether you remembered to close the garage door that morning. Slipping out of such conversations can be a useful skill, especially this time of year. Better if you can do it politely.

Fortunately, there’s a rejoinder tailor-made for truncating dull conversations. Just say “. . . before you launch into that, could I share some ideas I read about managing revenue risks?” The sort of thing you’d say to ditch an encounter on Chat Roulette if your mouse wasn’t working. You will be rewarded: “. . . Hey, I just saw someone who I really need to talk to. . .” Off into the crowd goes your new acquaintance, and her untold dermatological mystery, while you move on to the bar. You can thank me for the idea by sending a Starbucks gift card.

But let’s say, by chance, this individual happens to be a CFO or an enlightened VP of Sales for a fast-growing company who tells you, “Great! That could really help my company’s performance. I’ve got time.” Game on! You will be ready. And you can speak with the same passion and fervor as a TV evangelist, because once you’ve scratched away the dry wrapper, risk management is pretty darn exciting. You’ll want to begin by sharing best practices. But call them something catchier, like five killer risk rules your competitors haven’t yet figured out.

1. Define risk broadly. Don’t just provide a forecasting spreadsheet or draw a sales funnel on the conference room white board, and leave it at that. In fact, there isn’t anything in the breadth of Enterprise Risk Management that couldn’t have an impact on revenue. That includes strategic, financial, operational, compliance, and reputation risks. So if your sales strategy planning doesn’t consider all of these categories, you’ve left something out.

2. Recognize both the opportunities and downsides of risk. Many organizations think of risks as undesirable, as something to reduce or eliminate. But all organizations take on risks, and the most promising sales opportunities often involve heightened risk. The management challenge is to take on ones that align with the company’s overall strategy, and that are not too high for what the company can accept.

3. Develop a culture of identifying and evaluating risk at multiple levels in the company. A tough shift for sales organizations steeped in a can-do culture. While risk identification and evaluation aren’t the same as can’t-do, they are often seen that way: “Don’t tell me how you’re not going to make your number, tell me how you are!” One reason why many business developers rarely see the first warnings of risk. Risk assessment must be performed regularly in every department, but especially throughout Sales and Marketing—from telesales on up—so the most critical ones can be presented to decision makers.

4. Look at the total cost of risk. Risks that come home to roost compromise revenue, and increase marketing expenses for maintaining higher revenue-pipeline multipliers. But there are non-monetary ripple effects as well: lost productivity, distractions, low morale, and in the case of social media, negative publicity.

5. Senior management and business development staff must collaborate. “I don’t know exactly what they do over in Sales to make goal, but somehow, they always manage to pull it off at the end of the year!” The best companies take a different approach, recognizing that Sales is not a black box. By working together and constantly improving connected strategies and tactics throughout the organization, they are more likely to achieve success.

After you’ve shared these scintillating ideas, who knows where the conversation will go! But in case your friend says, “Thanks for the insight! Now, about the mole I was telling you about . . . . . ” maybe you’ll be lucky. If your timing is right, the caroling will begin.

Happy holidays!

Hiring Sales Talent for Your Start-Up? Look for More Than Just Great Selling Skills

Kyler is considering leaving his cushy sales job at an established company to sell for a startup. Will he be successful?

There’s reason for asking. Kyler’s skills are in hot demand. According to a recent article in Forbes Magazine, The Four Skills that Will Get You Hired by a Start Up, sales experience tops the list. “Most startups, whether they’re consumer-facing or B2B, are selling something and as such need effective salespeople. . . There just aren’t enough enthusiastic salesmen to go around, making this a qualified candidate’s market.” Go Kyler!

Can he make the leap? In his current job, Kyler prospects for new leads, qualifies opportunities, manages the sales process, and closes deals. Startups need people who can do the same things. This is a tad misleading though, like comparing freshwater fish to saltwater fish by saying both swim, lay eggs, and live in water. Plunk a creature from a freshwater habitat into the ocean, and you’ll observe that it doesn’t flourish. So if you’re a fish, simply being in water doesn’t count for much unless the chemistry matches your DNA.

Same for salespeople. The wrong environment can be suffocating, to say the least. And when it comes to selling products and services, it’s hard to find two environments more different than established companies and startups.

1. Startup salespeople wear multiple hats. Marketing department? What marketing department? Unlike larger companies, startups don’t partition job functions with crisp boundaries. A salesperson needs to be as adept at creating marketing collateral and writing blogs as meeting face-to-face with prospective customers and developing tactical account plans.

2. Startup customer references are scarce. Customer word-of-mouth marketing can be a powerful sales tool—when you have it. Established companies build strategies on it. “Our satisfied customers are our greatest sales asset.” But at startups, salespeople engage with prospects every day minus a trove of non-fiction customer success stories.

3. Prospects can be risk-averse about buying from startups. For some prospects, substitute terrified for risk-averse and you’ll have a better concept of the intensity. And while not every prospect shares his or her anxiety, it’s often manifest in other ways, like uncontrollable quivering. As a result, startup salespeople are practiced at saying “as a customer of our company, you’re not ‘just another account’ like you are with MegaCorp.” And they are absolutely correct.

4. Startup sales processes and pricing are often created on the fly—a great advantage for those comfortable with improvisation. When you’re not constrained by it’s-the-way-we’ve-always-done-it myopia, you can run circles around your sales process-bound competitors. On the other hand . . . in the heat of the decision moment, a sales rep who is accustomed to conforming to how things have been done in the past will resemble a deer in headlights.

5. Startups deal with copious amounts of sales trial and error. No biggie, but at startups, that approaches a 1:1 ratio. One company I worked for had developed a custom software solution for A lumber distributor (emphasis on the A!), and they wanted to sell that project as packaged software to a broad market which I’ll call—drum roll, please—lumber distributors! At first, we viewed that market as a single, undifferentiated group. I could create a massive PowerPoint detailing the nuances of lumber distribution, but mercifully, I have ditched the idea. For brevity, I’ll only say that while lumber wholesalers and lumber retailers both sell wood, they bear little in common operationally. Believe it or not, it took us quite a while, and a lot of selling expense, to figure that out.

6. Startup sales-cycles and projected sales rep OTE (on-target earnings) are SWAG’s—if that. Ah, yes! You knew it would be on the list, especially after all that trialing-and-erroring (see #5). To paraphrase from another context, “when you’re selling for a startup, the best way to make a small fortune is to begin with a large one.” It might take several quarters before realizing a payoff—when the first prospects become customers, and a salesperson deposits her first commission checks. No point for any party to get started if they can’t sustain the sales effort over the long haul.

Will Kyler be able to swim with the sharks as a sales rep for a startup company? Can he give up the resources his current employer provides, including his sales-qualified marketing-generated leads, ample customer references, and shiny promotional collateral? Can he go it alone without his annual three-day selling skills workshop and the trainer-provided Sales Process Roadmap on compact disc, still hermetically sealed in its original vinyl sleeve? What about trips to Aruba for making Club, and his more-or-less dependable commission checks? Probably gone, until his startup employer has the enviable problem of tripping over its own success, just like the large monolithic competitors it intends to upend.

Equally important, what should employers look for in startup sales talent? If we believe the Forbes article, we’d look for a “heavy hitter,” a strong “hunter” who can “close the deal.” It’s all good. But I’d be most comfortable with a candidate who also has startup success in his sales DNA.

Are You Mature Enough to Invest in Marketing Automation?

The word automation clanks like steel hitting steel—unemotional, cold, brutally purposeful. I see spindly robotic arms on perfectly straight assembly lines, tirelessly performing identical movements. Grab part #A-478 in metal pincers. Position onto 8 millimeter bolt. Rotate 4.82 revolutions. Repeat, ad infinitum.

Coupling flamboyant marketing to the un-sexy uniformity of automation seems oxymoronic. An emotional business discipline juxtaposed to a manufacturing practice that eschews emotion. Gigantic biz-dev systems chugging in a daily monotony. Warm and fuzzy lead nurturing functioning alongside hard and calculating data mining. If software could make noise, these systems would screech and hiss.

Still, we press on. “Do more with less!”—the raison d’être for automation, which clever people sell to business development executives, who then sell it to customers. Marketers often cloak automation in a digestible sugar-coated tablet called process innovation. I get it. Customer engagement that’s genuinely personal doesn’t scale. So, voila. Automation! Problem solved!

Well, not really. As Bob Thompson recently wrote in a blog, What’s Next for the Marketing Automation Industry, “After 10-plus years of development, Marketing Automation is not a particularly big space. Not even $1 billion in annual revenue with many small players.” Outside of high-tech, where analysts say marketing automation has achieved 50% penetration, “other industries won’t be easy to enter,” he writes. Why the slow uptake? According to Thompson, “this stuff is still way too complicated,” adding “marketing automation is just a piece of the digital marketing puzzle.”

Despite the quirkiness of tying two odd-couple words together, there’s nothing wrong with Marketing Automation. But we cleave to faddish techno-talk about its transforming power. Here’s an example: “This conversational marketing technology is easily integrated with all well-known CRM and SFA systems including, Oracle/Siebel Microsoft CRM Dynamics, and Pivotal CRM, with bi-directional synchronization between the SFA and the marketing data mart. Unified demand generation and lead management with CRM/SFA and lead scoring capabilities can help solve these challenges, and bridge the coordination gap that often exists between marketing and sales.”

Phew! Got that? In this case, the coordination gap begging to be bridged is between the automation geeks and marketing professionals.

A gap that will become gappier, because in the near future the likeliest buyers for automation technology won’t converse using arcane technology buzzwords and cryptic acronyms. Gartner predicts that by 2017, “Chief Marketing Officers will outspend CIO’s on technology . . . the onslaught of interactive marketing and digital commerce—starting with the Web and email and more recently venturing into mobile and social interactions with customers—is behind much of this technology spending,” according to an article in InformationWeek (Spend Trend, February 11, 2013).

Marketing automation must gain adoption from people outside the IT cognoscenti, and proponents will have to stop indiscriminately hurling wet technology pasta at the wall, impatiently waiting to see what sticks. Instead, they must first confront a marketing problem so obvious that few people see it: some people simply don’t give a tinker’s damn about marketing automation. Who are these people, and how can they be so oblivious?

For the answer, I borrowed a model called CMM—Capability Maturity Model—from Information Technology. In essence, the CMM identifies four levels of information technology use in business—Basic, Standardized, Rationalized, and Dynamic. At the lowest level, Basic, organizations consider IT a cost center. “Our IT plan for next year? Cut the department budget by 16%!” Convincing executives at such companies they need more sophisticated software compares to walking up to a squirrel and screaming “thirty-nine!” several times, hoping the confused animal will extract meaning and calculate something. I know from experience.

Move up the hierarchy from Basic, and IT deployment becomes more consequential—and more valuable—for enterprises. Organizations at the top level, Dynamic, use information technology strategically, inextricably embedding it in their brand, product or service. Netflix is a stellar example. You can find others next time you’re surfing the Web, or riffling pages in a trade journal. Nail a company’s CMM level, and you know whether its executives think of IT as just a mess of cables, connectors, and barely-usable software, or something that produces value.

Similarly, with business development sophistication, companies fit into different strata. And as with IT, some companies maintain resources, strategies, and tactics that are matched to their competitive situation–more or less. Their executives are less likely to show excitement when automation vendors knock–or rather, e-mail and Tweet. Others display palpable pain: “For the Nth consecutive quarter, our revenues did not meet plan.” Like CMM, the Sales Maturity Model (SMM) has four levels—Revenue Center, Efficient Revenue Center, Loyalty-driven, and Value-interdependency.

Revenue Center (CMM level Basic): Companies that regard their sales operations as Revenue Centers are product and transaction focused. They view customer purchases as the end-point of the sales process, and there is scant understanding of the buying process. Conversations with customers have ephemeral value because they concentrate on “closing the deal.” Revenue Center companies have a unilateral communication strategy that emphasizes “getting the message out.” Prospecting is a “numbers game,” and revenue gains are dependent on increasing the number of prospecting contacts. Information is stockpiled, with little information shared internally or with customers. There is weak collaboration between sales, service, marketing, accounting, and operations.

Efficient Revenue Center (CMM level Standardized): Efficient Revenue Centers operate in companies concerned with reducing selling costs, finding more productive ways to generate revenue, and increasing revenue per transaction. Companies seek “best practices” and tools that facilitate individual productivity and efficiency, and expect that increased profits will result. Efficient Revenue Center companies segment prospects into target markets, and understand which targets are likely to yield the greatest profits. Customer purchase decisions are largely seen as the domain of individual “key decision makers,” and tactics tend to ignore the dynamics of buying networks in purchasing. Channel selling strategies are not tightly integrated with direct sales operations.

Loyalty-driven (CMM level Rationalized): Companies that are Loyalty-driven have transitioned from product-centric operations to customer-focused. Loyalty-driven companies want customers that are not only likely to repeat purchases over time, but will become enthusiastic product evangelists. They build corporate culture around the ideal of customer centricity. Loyalty-driven organizations have adopted processes for communicating and listening both internally and externally, sensing and responding to customer problems, and maintaining high-quality end-to-end customer experiences. They measure success not only on revenue received, but on value delivered. Marketing and sales use longer planning horizons, and purchase transactions are considered events on a customer-relationship continuum—not as a process end point. Information is shared within the company, as well as with customers and channel partners.

Value inter-dependent (CMM level Dynamic): Value inter-dependent companies have a unique feature: it can be difficult to distinguish between vendor and customer. Selling and buying processes are tightly integrated. Companies that are Value inter-dependent engage in co-creation of products and services, and each organization has a strategic stake in the other’s success. Networks of people from multiple departments engage in collaborative teams, and there is open sharing of ideas for innovation, revenue generation, and cost reduction. Information tends not to be stockpiled, but flows freely between organizations. The interactions of social networks are well understood, and people are valued for specific skills and capabilities, rather than seen as “targets,” or simply job titles. Value is transferred as much through “relationship capital” as through products and services.

The mistake I see so often is making the techno-chauvinistic assumption that every company strives to hold a coveted spot on the top rung of the maturity model. Anything less constitutes a flawed business plan. But the issue isn’t whether there’s a right or wrong maturity level, or a good-better-best. Instead, a company’s sales maturity level must at least match the market situation in which it competes or will compete. If uncorrected, any gap will create a revenue trajectory that won’t be pretty. While companies at the Revenue Center level are not necessarily automation luddites, they tend to have less of it than those at higher levels. As companies move up the hierarchy, you often find marketing automation more integrated and more embedded in the work people perform—for collaboration, workflow, analytics, planning, and decision making.

Still, a company’s maturity level has less to do with the marketing automation it uses, and everything to do with how executives think about revenue. Specifically, how they think about business growth, value delivered to customers, value returned to the organization—and role of business development for achieving each of these.

Customer Information Power: An Obvious Illusion

The Chevy Nova failed with Hispanic car buyers because the nameplate—no va—had the unfortunate coincidence of meaning doesn’t go in Spanish. Proctor & Gamble’s Ivory Soap owes its buoyant characteristic to a serendipitous production error. Coca Cola’s 1985 introduction of New Coke was a marketing ploy to increase sales for its predecessor, Classic Coke.

As we say in sales, “if you believe that, I have swamp land in Florida to sell you!” Each story has been debunked on Snopes.

Another myth belongs in the same group: “In today’s environment, information power lies firmly in the hands of your prospects and customers.” It’s hard these days to read a marketing, sales, or social media blog that doesn’t include a flavor of that proclamation. Vendors must crave being whipped into submission, and bloggers are eager to oblige. “I cannot understand why marketing and sales folks continue to think and act as if they had the power,” marketing strategist Rebel Brown wrote in 2012.

Forget the popular hype—vendors still have information power, and plenty of it. In the battle for information supremacy, I’ll choose PhD data scientists, petabytes of customer information, and sophisticated predictive analytics over Joe the Purchaser, his access to online product reviews and his trusted social connections.

Recent news stories underscore this point. Customer information power? See if you can find any:

What Cruise Lines Don’t Want You to Know. If it’s safety-related, plenty. At a recent US Senate hearing, cruise expert Ross Klein, a professor at Memorial University in Newfoundland, said 79 fires have broken out on cruise ships between 1990 and 2011.“Most of these fires have received little coverage in the US press. It is a topic that the travel publications avoid and travel agents do not like to hear,” according to an article on Information avoidance means less searchable content. At least Mr. Klein’s website,, includes data about accident reports and ship inspection scores from the Center for Disease Control and Prevention (CDC).

But what if you wanted to learn more by looking elsewhere? Just for the heck of it, I checked the website for The Cruise Line Industry Association, which represents 26 companies, including the biggest, Carnival and Royal Caribbean. It offered no results when I entered ship fires in the search box. Amazing. (Interestingly, the word fires yielded some great travel destinations, but alas, no safety information.)

The Extraordinary Science of Addictive Junk Food. (The New York Times Magazine, February 20th, 2013) Author Michael Moss wrote a sentence that jumped right off the page and hit me in the head: “What follows is a series of small case studies of a handful of characters whose work then, and perspective now, sheds light on how the foods are created and sold to people who, while not powerless, are extremely vulnerable to the intensity of these companies’ industrial formulations and selling campaigns.” The not-powerless-but-extremely-vulnerable part struck me, especially in the same sentence as selling campaigns. And what is a selling campaign without asymmetrical information?

The article quotes Bob Drane, Oscar Mayer’s former Vice President for New Business Strategy and Development, and creator of the popular Lunchables product line: “What do . . . MBA’s learn about how to succeed in marketing? Discover what consumers want to buy and give it to them with both barrels. Sell more, keep your job! How do marketers often translate these ‘rules’ into action on food? Our limbic brains love sugar, fat, salt . . . so formulate products to deliver these. Perhaps add low-cost ingredients to boost profit margins. Then ‘supersize’ to sell more . . . . and advertise/promote to lock in ‘heavy users.’ Plenty of guilt to go around here.”

Push to Gauge Bang for Buck From College Gains Steam (The Wall Street Journal, February 12, 2013) “High school seniors now trying to decide which college to attend next fall are awash with information about costs, from dorm rooms to meal plans. But there is almost no easy way to tell what graduates at specific schools earn—or how many found jobs in their chosen field.” “Was college worth getting in the amount of debt I’m in?” one student asked. “At this point, I can’t answer that.” Pop quiz: who has the information power in this scenario?

“Last spring, the Obama administration began developing a ‘College Scorecard’ that would add salary information for graduates and average debt load to existing data . . .” the Journal article says. My home state of Virginia is one of the first states to publish salary data for graduates from its colleges and universities. According to one senior, “It’s much easier to plan when you have this information.”

New Vehicles Collect Data, the Destination of Which is Yet Unknown (The Washington Post, March 7, 2013) “Cars have long gathered data to monitor safety and performance. But their new found connectivity may allow a range of parties—automakers, software developers, perhaps even police officers—new access to such information, privacy advocates say. Because few US laws govern these issues, consumers have little control over who can see this data and how it can be used.” One Ford technologist attempted to allay consumer concerns: “We assume that you’re comfortable with whatever privacy policy [an application] has.” Thank goodness! For a second, I thought I lost my information power!

“The widespread embrace of social media has put even more information – and ultimately power – in the hands of the buyer, and that has drastically altered the jobs of the salesperson and the marketing professional,” Marketo’s Phil Fernandez wrote in a blog, What the iPad Revolution Means to The Future of Sales and Marketing. An exuberance that contributes to the myth of customer information power, and leads to another confusion: information access doesn’t equate to information power.

Steven Rosenbush and Michael Totty wrote in today’s Wall Street Journal that “companies have access to vastly more information than they used to, it comes from many more different sources than before, and they can get it almost as soon as it’s generated.” According to the article, Facebook’s daily data analysis generates about 500 terabytes of new information every day. Against the corporate nuclear arsenal of Big Data, Joe the Purchaser’s online searches via mobile web browser compares more to a pea shooter.

On beyond Facebook! “Businesses in a slew of industries are putting [big data] front and center in more and more parts of their operations,” the article reports. Meanwhile, the power challenge facing consumers is less about a lack of information than structural impediments to uncovering, organizing, and interpreting what they find. Then there’s that nagging question of personal will. How inclined is a high school student standing in front of a vending machine to look up nutritional information about the bag of Doritos she’s about to purchase right before volleyball practice? She’s carrying an iPhone, but she needs a snack and has three minutes before she has to be on the court. “Insert $1.00 and press U-5.” Sold!

I find customer information power more theory than reality. Snack foods, higher education, personal transportation—huge mature industries, each one. In 2011, there were 16 million cruise bookings worldwide. Today, you’d expect customers to be information-power dominant, especially given the ballyhoo over Customer 2.0, and the ubiquity of web access.

But there are plenty of impediments that make customers decidedly un-powerful. Choppy regulatory oversight with higher education and the cruise industry. Tight vendor control over product information with snack foods. The question of data ownership in automotive and personal transportation. Not to mention the flying mallet called Big Data that has swirled into the picture. For now, vendors—not customers—own that hammer. And that’s a huge advantage.

Customer information power? I don’t see it. But don’t take my word for it. Wait a month or two, and you can check it on Snopes.

Your Sales Forecast Accuracy Sucks – and Why It Doesn’t Matter

“If you’re on the forecast accuracy horse, it’s dead. Get off!” says Dave Garwood, of R. D. Garwood in Atlanta. His mellifluous baritone could sell gilded steak knives to vegetarians. But Garwood is a manufacturing guy, not a sales executive. In 2000, he became one of a handful of people to be honored with the prestigious Lifetime Achievement Award by the American Production & Inventory Control Society (APICS).

“I can’t think of a way to clear the room faster of salespeople than to bring up sales forecasting,” Garwood says. I’m not surprised. The perennial scapegoat for inaccurate forecasts has been the sales professional, who gets kicked in the rear after management compares forecasts to actual results. Sometimes before. “How can you put THIS on your forecast? . . .”

The beatings will continue until morale improves. Senior executives have been sold on the need for forecast accuracy for as long as they’ve been moaning about why they can’t seem to achieve it. The quest for forecast accuracy is futile. As Garwood points out, the purpose of a forecast is to get to a set of numbers that are reliable—to “reduce variation, not eliminate it.” Tell it, RD!

For many salespeople, accuracy is embedded right into the sales job description: “The Local Sales Manager will conduct sales training, sales meetings and weekly one-on-one meetings for sales staff and must be able to forecast accurately and maintain excellent client relationships.” No doubt the company that posted that opening has a lovely pond for its employees to walk across.

Sales forecast accuracy seems the Holy Grail. Blogs and videos tout ways to gain the required clairvoyance. “A lack of discipline around sales forecasting can kill your sales organization’s credibility,” Matt Heinz wrote in a blog, Seven Steps to Greater Sales Forecast Accuracy. He’s right, but other forecasting impediments are more consequential.

“The accuracy of most forecasts depends on decisions being made by people rather than by Mother Nature. Mother Nature, with all her vagaries, is a lot more dependable than a group of human beings trying to make up their minds about something,” Peter L. Bernstein wrote in his book, Against the Gods. The Remarkable Story of Risk.

In my experience, the most overlooked cause for sales opportunities coming undone is that unpredictable [stuff] happens. Example:  Stefano, a top-producing sales executive, forecast a $500,000 enterprise software opportunity to close in the current quarter. He had been working it for a year, and had built solid relationships with the buying team. But two weeks before the anticipated order date, the client’s project manager announced he was leaving for a mountain biking trip in the Andes with his girlfriend—effective immediately. He bought a one-way ticket, and offered no commitment on a return. Then, three days later, the client announced the delay of a major product release after a key electronic component was no longer available from the supplier. Testing a substitute from a backup supplier was expected to take six weeks.

Concerned about cash flow, and not knowing when the project manager would tire of his South American adventure, management decided to “put all IT projects on hold.” All the discipline and predictive analytics in the world couldn’t change the outcome: Stefano incorrectly forecast a hefty chunk of revenue. He is remembered at his now-former company as a bum.

Stefano’s story is anecdotal, but it reminds us that more often than not, buying decisions hinge on unforeseen events that are out of anyone’s direct control. And even the most sophisticated statistical algorithms and predictive analytics can’t account for unanticipated events—what Naseem Taleb calls Black Swans. Loss of key personnel. Supply chain disruptions. Natural disasters. Mergers and acquisitions. Consequences from energy disruptions, strife in Syria, and antagonism between the Koreas . . . It’s a very long list. Oh, I nearly forgot China.

Taleb’s Black Swans have three attributes that are familiar to salespeople: “First, [the Black Swan] lies outside the realm of regular expectations, because nothing in the past can convincingly point to its possibility. Second, it carries an extreme impact. Third, in spite of its outlier status, human nature makes us concoct explanations for its occurrence after the fact, making it explainable and predictable,” he writes.

The problem is, management insists on good predictions, feeding a vicious cycle of forecasting, planning, experiencing performance gaps, and recovering from operational mistakes. Repeat. As author Nate Silver wrote in The Signal and the Noise, “If you can’t make a good prediction it is very often harmful to pretend that you can.” Most people pretend. It’s bad for a person’s career to suggest otherwise, especially the first day on the job.

Forecasting got its start a long time ago, when people recognized fate alone didn’t govern outcomes. “Capitalism could not have flourished without two new activities that had been unnecessary so long as the future was a matter of chance or of God’s will. The first was bookkeeping, a humble activity but one that encouraged the dissemination of the new techniques of numbering and counting. The other was forecasting, a much less humble and far more challenging activity that links risk-taking with direct payoffs,” Bernstein wrote. Silver adds to this idea: “Forecasting reflected the new Protestant worldliness rather than the otherworldliness of the Holy Roman Empire. Making a forecast typically implied planning under conditions of uncertainty. It suggested having prudence, wisdom, and industriousness . . .”

Interesting that neither author chose to mingle the word accuracy in these explanations. Though as Silver points out in his book, accuracy has become implicit in forecasting. He devotes considerable effort in developing that idea when he describes the science of weather forecasting. But people mistakenly conclude that forecasting weather and forecasting decisions are similar.   In fact, “there’s very little that’s really predictive,” says Jan Hatzius, Chief Economist at Goldman Sachs. “Figuring out what’s truly causal and what’s correlation is very difficult to do.”

“What happens in systems with noisy data and underdeveloped theory [such as B2B decision making] . . . is a two-step process. First, people start to mistake the noise for a signal. Second, this noise pollutes journals, blogs, and news accounts with false alarms, undermining good science and setting back our ability to understand how the system really works . . . As the memory of our mistakes fades, the signal will again seem to shimmer over the horizon. Parched for prediction we will pursue it, even if it is a mirage,” according to Silver.

Good forecasts depend on making informed judgments. Judgments which rely on assumptions and past data that may no longer be relevant.  “It should be a given that whatever forecast we make on average will be wrong . . . so usually it’s about understanding how it’s wrong, and what to do when it’s wrong, and minimizing the cost to us when it’s wrong,” said Dr. Alex Ozonoff, an epidemiologist at the Harvard School of Public Health.

Something to remember the next time your CFO asks, “why can’t we ever get accurate sales forecasts?”

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