Category Archives: Revenue Risk Management

How to Make Invisible Value Visible

Thursday, 26 May 2016 17:30
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And now for my next act . . .  in just nine words, I will transform a sack of brown beans into an aspiration.

“It’s not a cup of coffee, it’s a lifestyle.”

Go me! Try that with artificial intelligence! Over centuries of trade, we marketers have not only mastered principles of supply and demand, but how to craft a killer product pitch. “This obsidian buffalo hide scraper is unlike any hide scraper you’ve ever used!” No doubt a speil familiar to our ancient ancestors.

Our cleverness aims at avoiding a persistent fate that has existed since the dawn of commerce: getting dragged into the Abyss of Sameness. An omnipresent danger, even today. My perfunctory online research provides a glimpse into our fear: Products are becoming commodities receives 2,320 search results. Twenty percent more than I forgot my wife’s birthday, which gets 1,830. Business executives stress over commoditization, and its undesirable accompaniments: low margins, knock-offs, customer churn – and, if you’re a vendor, the dread of hearing, “yeah, everybody sells pretty much the same thing . . .” Please, no!

What’s in the Can? In 1980, I began a job managing IT for Graphic Fine Color (GFC), a printing ink manufacturer. If you’re not bowled over with intrigue, you’re not alone. But you also have insight about GFC’s marketing problem: ink is pretty blah. What could be more banal than a gloppy liquid that few people see before printing presses spread it onto business forms, brochures, product labels? I’ve tried explaining the product to friends. I’ve broached the subject with strangers. Same result: nobody notices ink, or cares much about it. But, if you’re willing to endure my passionate soliloquy on the topic, you will know by the end there’s nothing ordinary about this ubiquitous substance, or its manufacture.

GFC had a wonderfully interesting story to tell its customers. So in 1982, it created a low-budget marketing piece that I keep on my desk. An 8-page booklet titled, What’s in the Can? End-to-end, the booklet contains about 100 words and about 50 black-and-white photos, and takes less time to read than Goodnight Moon. But given its brevity, What’s in the Can? releases a flood of pent-up value.

Each picture shows employees performing different jobs. Weighing, mixing, milling, labeling, shipping, quality assurance, product development, accounting, and on-site customer support. Even sales! What’s in the Can? doesn’t include chemical formulas. You won’t find any explanatory captions, hype, self-assigned praise or customer testimonials. None are needed. Pride oozes from every photo. Since I left GFC, I have never looked at a five-pound can of Pantone 188 red the same way.

Problem solved. What’s in the Can? made invisible value visible – a plucky achievement for a small, hole-in-the-wall industrial manufacturer back in the marketing stone ages – the time before social media and big data made CMO’s into IT demigods. Fast forward 30 years to 2012, and we hear Facebook’s VP of Engineering, Jay Parikh, opine a similar challenge about value. In a few months, he said, “no one will care that you have 100 petabytes of data in your warehouse.” I know that feel, bro. But don’t worry. If you can make invisible value visible for printing ink, you can do it for anything.

Here are four valuable things that could be concealed inside your product, along with ways some companies have made them visible to customers:

Data and Information: “CIOs, CFOs and, increasingly, CMOs know data has value. The key is figuring out how much value,” wrote Nicole Laskowski in an article, Infonomics Treats Data as a Business Asset. “More than 80% of business executives surveyed by Gartner believe data is on the balance sheet, tucked under other intangible assets.” In fact, this is not true, according to Gartner Analyst Doug Laney. Even companies like Facebook, Google, and Nielsen do not monetize their data anywhere on their financial statements. This is odd, considering that it meets the accounting definition of an asset: a) it can be exchanged for cash, b) it can be owned by an entity, c) it generates probable future benefits (Gartner).

Companies are finding ways to release the value of data through providing it to customers. General Electric offers customers insight about probable failures through embedded sensors in equipment, and advanced analytics. “Even a seemingly low-tech company like John West, a U.K. canned-seafood manufacturer, is figuring out how to use data to enhance the customer experience. To provide visibility into its sustainability practices, the company tags the fish it catches, gathers data on where its fish are caught and then makes that data available to consumers. The consumer may not be purchasing company data outright, but the data is helping sell the product,” according to TechTarget.

On the other hand, the aftermath of the Apple-FBI case has created new caution for application developers, who are “racing to employ a variety of tools that would place customer information beyond the reach of a government-ordered search,” according to a May 25, 2016 Washington Post article, A Shift Away from Big Data. “The trend is a striking reversal of a long-standing article of faith in the data-hungry tech industry, where companies including Google and the latest start-ups have predicated success on the ability to hoover up as much information as possible about consumers . . . The sea change is also becoming evident among early-stage companies that see holding so much data as more of a liability than an asset, given the risk that cybercriminals or government investigators might come knocking.”

Product durability and quality. How many prospective customers think about – let alone know about – components that churn deep within a product? Mostly, buyers just want their purchase to work right out of the box, and they pay fleeting attention to a product’s innards.

Manufacturers have responded through improved engineering quality and materials. Those not only benefit consumer experiences, they save manufacturers significant expense for warranty service and product returns. Some products have become so dependable that consumers are no longer delighted. That creates a sales issue: how to get customers excited when a product simply turns on, runs, moves, behaves, or performs exactly as expected.

Auto makers, for example, have practically eliminated body rust and transmission breakdowns. But today’s buyers aren’t wowed. They’ve moved on, craving amenities like spacious cup holders plentifully scattered throughout the vehicle, Bluetooth connectivity, and nifty interior lighting. By 2025, consumers will even yawn at gas mileage ratings. “Who cares? Every car gets over 54.5.”

Car companies solved this selling issue by repackaging the value of product durability into something that consumers can appreciate without having to pop the hood or crawl underneath a car: plump warranty extensions. Subaru now gives warranties of 5 years or 60,000 miles covering “the engine block and all internal parts, cylinder heads and valve trains, oil pump, oil pan, timing belts or gears and cover, water pump, flywheel, intake and exhaust manifolds, oil seals and gaskets.” The average buyer won’t invest time learning what a flywheel does, where it is, what it looks like, or what it’s made of. They won’t memorize a list of components they won’t likely ever see. But they will latch onto “5 years, 60,000 miles. No extra charge!”

Employee loyalty and rapport with customers. These valuable characteristics are not always immediately visible to prospects. But a software company I worked for leveraged this strength through a seemingly-generous contract term: in the first 12 months of implementation, customers could receive a full refund for the software – which could cost up to $500,000 – if they were dissatisfied for any reason. In fact, company’s risks were ridiculously low. The trick – if you want to call it that – was that in over 10 years, no customer had ever requested a refund.

Large software implementations can be infamous for glitches, gotcha’s hiccups, fits, starts, and bugs. A dollar for every time a newly-installed customer began a conversation with, “But I thought . . .” would buy my family a nice dinner out and theatre tickets. The software company’s ability to bring qualified staff to customer projects – and to retain that staff over full implementations – enabled rapport and trust that customers were loath to break. Prospects loved the satisfaction-or-your-money-back assurance before accepting the uncertainties of a massive project implementation, and it was easy to provide.

Corporate Social Responsibility, honesty, and ethical sourcing. Head to the website of Oboz – short for Outside Bozeman (Montana) – and you will read: “When you buy a pair of Oboz [footwear], we plant one more tree.”

Visit Organic Valley’s website, and you’ll see a lovely photo of wind turbines, adjacent the message: “As farmers, we work closely with the Earth and Mother Nature—and we need to take care of the soil that feeds us. It’s our mission to reach a fully sustainable operation, from our farms to our offices, and through every step of our supply chain.”

Apparel maker Patagonia touts its products as Fair Trade Certified, and shares its commitment to paying its employees a living wage.

Until recently, few cared whether purchases had direct connections to environmental sustainability, employee well-being, or labor practices in a faraway continent. But today, those things matter. In many instances, Corporate Social Responsibility (CSR) has become so intertwined with products, the two can’t be teased apart.

Awareness of CSR skyrocketed in 2013, following two horrific events. First, in April, a factory in Bangladesh suffered a building collapse that killed over 1,100 workers. Americans learned that Walmart had been a major customer for the factory’s output, even though Walmart stated that it was “unaware that their apparel was being made in such factories,” according to an article in The New York Times . Then, Apple faced allegations of child labor, forced overtime, and illegal 66-hour working weeks at factories that were producing its beloved iPhones.

Overnight, knowledge about human suffering made it less fun to diddle on iPhones, or to crow about bargains on kids clothes. People faced a new conundrum, happily absent when supply chains were more opaque: if we choose to be ignorant of the misery others incur to make the things we might want to buy, what does that say about our humanity?

So, it’s not surprising that for some companies, ethical conscientiousness has emerged from its hiding place in the executive suite, and moved into the forefront of sales and marketing. This is a positive development, as it has led executives to voice unequivocal stands on important social issues that matter to employees, customers, and communities.

What’s unclear is how a company’s well-intentioned ethics sway customer buying decisions. For example, a 2012 survey by Perception Research Services International reported that while 76% of consumers indicated that they would be more likely to buy a product bearing a Made in USA label, but “just 21% said they would definitely pay slightly higher prices to buy American-made products.”

The Abyss of Sameness. Commoditization. The perception that products lack differentiation. These conditions represent failure to find and expose hidden value. If executives want to avoid these circumstances, and create value for customers, they will find opportunity by examining “what’s in the can,” and innovating ways to release it.

The Dark Side of Online Lead Generation

Monday, 16 May 2016 15:13
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Comedian Jerry Seinfeld made banality funny, but marketers exploit it for darker purposes.

Consider a Tweet I made recently: “I’m walking to Whole Foods after work to buy a 6 of local-brew #IPA. Suggestions?”

Without realizing it, I saturated this 81-character message with personal details, and shared it to the world:

1. I am over 21.
2. I live in an urban area.
3. I am employed.
4. I have discretionary income.
5. I drink beer.
6. I drink at places other than bars and restaurants.
7. I know people who have similar interests.
8. I seek the opinions of others online.
9. I am not brand-loyal when it comes to beer.
10. I am able to carry at least six pounds.

“There are eight unique data points per Tweet,” said Adrienne LaFrance, Staff Writer for The Atlantic. Here, I found ten, and my Tweet had capacity for 59 more characters. Lucky that I didn’t use them. Who knows what else I could have revealed.

Based on my innocuous Tweet, marketers can deduce that the car I drive isn’t a Hummer or a Cadillac Escalade. They can bet that I have a college degree. But that’s beside the point. They already know. Remind me again who has the information power, because it’s not me.

Every second, about 6,000 Tweets pulse through Twitter. Marketers mine this noisy digital exhaust to extract fuel to power their ravenous revenue machinery. Automated algorithms work 24/7 assembling details about individual human beings. By combining online and offline information about people, companies called list brokers create large files of personal artifacts. This information gets passed through a serpentine value chain, where it’s divided, changed, enhanced, and re-combined with more data. What gets harvested can be described as digital gold: richly-detailed profiles of consumers. List brokers package them into tidy, organized, fungible groupings called lead lists, vital for business development. Rube Goldberg would be proud.

But Goldberg’s whimsical imagination mimicked the physical world, where noisy events happen in plain sight. Lead generation processes depend on subterfuge. Prospect curation machinery works cleanly and silently, away from the public eye. Consumers are unaware about who (or what) collects their information, or who gets to use it. Reason #412 that I don’t wear a Fitbit, play online “brain games,” or use gene testing services. None of these businesses are required to comply with patient-privacy laws in the 1996 Health Insurance Portability and Accountability Act (HIPAA).

Many expectant or postpartum parents would be surprised to learn that their personal identities have been meticulously collected, and electronically shipped to and fro. Their names, and a whole lot more, are regularly sold to businesses, including eager telemarketers and digital agencies. For example, Dataman Group can sell you a New Baby List, which includes pre-natal families. Among the fields are contact information, home ownership data, dwelling unit type, estimated household income, number of months until birth, and whether the birth is (or will be), the mother’s first.

Dataman’s website makes a flamboyant appeal to its prospective customers:

Almost 1 out of every 2 births today is a first birth, creating enormous marketing opportunities.

Most first-birth families are also two-career families; working moms and dads with large, disposable incomes and no brand loyalties where child care products are concerned.

As a market, these growing families outspend childless couples 2 to 1 and are prime candidates for not only a full range of baby products, but also day care, home entertainment, photography, insurance, recreation, and catalog offers. Information on any product that your company offers that can offer these young families a better way of life will be welcomed.

No other life cycle list offers the accuracy, cost-efficiency or selections of OUR new parents mailing lists or prenatal list. You can even select Pre-Natal households by trimester….or New Babies by actual month-of-birth.

At the end of this sales pitch appears a curious request, one that hints at nefarious use: “Note: Sample mail piece and/or telemarketing script required on all orders with Children information. We support responsible marketing!”

Here is where things turn rough. With a selection tweak or two, marketers can bubble up motivated buyers – say, mothers in the third trimester, or people living more than one mile from a playground. So far, so good. But with additional tweaks, marketers can find greater buying urgency by exposing a related demographic: vulnerable buyers. Some more tweaks to reach buying motivation’s top rung: The Desperate. A lucrative target with tantalizingly short sales cycles, little comparison shopping activity, and low customer information power. All it takes to get the cash machine spinning is an appealing product, a little imagination, and the right search criteria.

How about targeting single moms below a certain income level, living in the 22 states that have declined Medicaid Expansion? That information would be attractive to rental appliance and furniture outlets, credit card companies, and loan providers. A warping of the ideal, “give customers what they want.”

This is the way revenue generation works in the digital age. A single New Baby lead list supports everything from aspirational selling to predatory marketing. Innovative baby backpacks to take small children on fun adventures,  or payday loans for food and rent payments when cash runs out. Which way you go depends on what you’re selling, and how you sort and select the prospects.

Information that list brokers use sometimes comes from landing pages designed to surreptitiously collect personal information, which then gets sold to others. When I entered the phrase, need money for food, into a search window, I received advertising links that assumed ancillary concerns: “Bad credit personal loan,” “500 to 20000 personal loan,” “sell your house fast,” and “are you eligible for aid?” These are emblematic of the marketing predations that occur, often in plain sight. The last ad, linking to a website ending in dot-com, clearly wanted to find out more about me. I did not click on it.

When I re-entered the same search phrase one hour later, the aid-eligibility ad had vanished, presumably because Google recognized the ruse, and removed it. In fact, in 2014, “Google removed 524 million advertisements and banned more than 214,000 advertisers from its search results. But predatory companies are still finding loopholes,” LaFrance wrote in an article, How Google Plays Whac-a-Mole with Shady Advertisers. Squashing 524 million ads per year equates to around 1,000 ads per minute. That’s a lot of Whac-a-mole.

I conducted this search as a simple experiment for this article. But what if my query was genuine, and my situation perilous? What if I proceeded to fill out the form? Who would have my information? What would I unleash? Sadly, there are few laws protecting prospects. Congress hasn’t passed a consumer privacy law since 2009. This, despite huge increases in social media use, advances in data science, and wide adoption of marketing automation. At least my beer purchase was discretionary. Vulnerable prospects face privacy hazards that are more poignant.

“This process for collecting customer data exploits a loophole in consumer protection laws. Companies can buy lists of people who have asked about diabetes, Alzheimer’s, or Parkinson’s disease. They can learn about victims of assault and people diagnosed with HIV,” said Aaron Rieke, Project Director at Upturn. Rieke was a panelist on NPR’s Tech Tuesday program, When Companies Use Your Online Searches Against You (November 10, 2015). “How did they get my name?” Amazement that happens all too frequently online.

It’s not just from hijacking customer trust, and stealthily scraping information from online forms. In 2013, 43% of free health apps sold users’ personal data, according to a study by the Privacy Rights Clearinghouse. “Fewer than half of mobile apps that collected health and fitness information provided a privacy policy in which they spelled out how user data could be shared, and 43% of free apps tested by the group shared personal information with advertisers,” The Wall Street Journal reported in April, 2015.

“The extent of consumer profiling today means that data brokers often know as much – or even more – about us than our family and friends, including our online and in-store purchases, our political and religious affiliations, our income and socioeconomic status, and more,” said FTC Chairwoman Edith Ramirez. “It’s time to bring transparency and accountability to bear on this industry on behalf of consumers, many of whom are unaware that data brokers even exist.”

“Technology gives us power but cannot guide us as to how to use that power. The market gives us choices but leaves us uninstructed as to how to make those choices,” Lord Jonathan Sacks wrote in his book, Not in God’s Name: Confronting Religious Violence.

Those conundrums occur every day in marketing. “We’re doing this because we can,” clients tell me when discussing their marketing strategies and tactics. I urge them to include an additional hurdle. “Ask yourselves, ‘what is the right thing to do?’

Note: this article was published on CustomerThink. To read the original column, please click here.

Are Salespeople Making Good Bets for Your Revenue Pipeline?

Monday, 16 May 2016 13:39
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Many years ago, New England Life Insurance, now part of MetLife, developed a series of cartoon ads that was witty and terrifying.

Each ad had a formulaic depiction of a person saying the caption, “My life insurance company? New England Life, of course. Why?” The situations varied, but the brilliance was that the reader could see always see an inevitable calamity about to befall the utterly oblivious central character. “Scare the living [bleep] out of people,” someone must have advised the creative director at the agency, “but in a jovial way.” Ha ha.

The vignette I remember best portrays a well-dressed executive in a sleek, all-glass corner office near the top of a skyscraper. He’s seated in a swivel chair chatting on the phone, his feet propped on his desk. Meanwhile, in plain view behind him, an errant half-ton wrecking ball attached to a crane is about to crash through his window. “My life insurance company? New England Life, of course. Why?” Somebody, please! Warn this man!

That visage represents the planning perils that CFO’s and other senior executives face. CFO’s feel confident when projected revenue aligns with targets. But too often, the risks are opaque. Watch out for that wrecking ball! Revenue projections are cleansed of the many uncertainties that lurk throughout the sales funnel. When I recently asked on several LinkedIn forums about whether anyone worked with a CFO who had influence over sales lead qualification practices, a reader question ricocheted back immediately: “Why would a CFO need to be involved in this?” His was the only response.

But it corroborated an observation: In most organizations, CFO’s do not guide the routine revenue bets that salespeople make. How confident can CFO’s be about the efficacy of sales force decisions? How do they know that the risks salespeople accept are ones the company can absorb? For example, one salesperson might have few scruples when accepting new leads: “Hey, if this deal closes, I make a boatload of commission. If not – adios! I was on my way out the door, anyway.” Her colleague might hew to a different risk viewpoint, unwilling to prospect new opportunities in favor of tending his cash cows. The moment those cows cease being reliably productive, he too will probably move on. Other reps, browbeaten by management’s obsession with hitting pipeline targets, might doggedly seek large, but highly uncertain, long-term deals. The pay bonus the company provides them for fattening the revenue pipeline cements the behavior.

Such risks seep covertly into cash planning worksheets, and CFO’s, feet propped on their desks, are sitting on all of it. “Projected Q4 Revenue, Northeast Region.” All the CFO sees is a single-integer aggregation, combining oodles of sales judgements. Smatterings of learned experience and buckets of wild hope – it’s all in the number.

Too much risk in the sales pipeline can create cash planning disasters. So can too little. How do companies manage this yin-yang? How should the most revenue-focused parts of the organization – Finance and Sales – collaborate on managing uncertainty and risk? I asked CFO-novelist Patrick Kelly, an experienced tech executive who has managed several IPO’s, for his thoughts. “Cash flow projections are the CFO’s responsibility,” he told me. In general, “a CFO needs to be involved in the mechanics of a sales funnel, but not in the details of qualification.” In other words, CFO’s need to understand how sales cycles work, how long it takes to close deals, and the percentages of leads that progress through each stage of the sales process, but they don’t need to be involved in the minutia of scoring leads and developing qualifying questions.

Kelly explained why knowledge about sales funnel mechanics is so crucial. “When Sales reports revenue projections to Finance,” he said, “Sales is going to say ‘everything looks great,’ but it’s the CFO’s job to have his own point-of-view,” and to use that perspective for making adjustments. “It’s not uncommon for a CFO to reduce the revenue forecast he or she reports to the board,” he told me. For example, Sales might forecast revenue to a Nigerian subsidiary of a multi-national corporation for the current quarter, but Finance might not include the opportunity for cash planning because the effect of low oil prices on the Nigerian economy could likely cause a purchase delay, or could scuttle the sale altogether. In essence, a CFO can translate what might have been an unanticipated wrecking ball to a cash flow plan into a recognized force against revenue. A force that he or she can possibly manage, especially when it’s anticipated early enough.

But what happens when Finance and Sales work in thick, impenetrable silos, and don’t regularly exchange meaningful information about revenue uncertainty? For example, when I mentioned the disparate criteria that reps within the same company use for accepting sales leads, Kelly acknowledged that a lack of risk standards could be problematic for cash flow planning. But he said that at smaller companies, silos are flimsier, and CFO’s tend to know useful details about individual revenue opportunities. At large companies, however, CFO’s cannot easily monitor the risk profiles for hundreds, or thousands, of pipeline opportunities. While low- and high-risk conditions among a large set of deals generally offset, that doesn’t mean the “average” risk among that group falls within an acceptable range for a CFO planning her company’s revenue flows.

This condition damaged a software company I worked for. The sales pipeline was fat, but customer buying cycles were painfully long, and opportunities did not convert quickly enough to satisfy the company’s ravenous hunger for cash. Finance was starving for money, but the CFO was oblivious to the pipeline risks. All she saw was a plump number on a spreadsheet representing next quarter’s revenue. Based on its cash position, the company had low risk capacity, and it would have been better off motivating the sales force to close lower-revenue deals with shorter cycles.

Sales never got the message. Instead, managers urged reps to hunt for revenue opportunities in the tangled thicket of big, bureaucratic Fortune 500 customers. A perilous high-risk, high-reward strategy for many companies, but disastrous for ones that can’t sustain the investment. In the end, the company laid off most of its sales force, canned its president, and reorganized the remaining management team. The terse press release did not mention anything about pipeline risks, just “Revenue did not meet expectations.” There’s always a back story.

Some companies commit to slogging through long buyer journeys and procurement cycles through maintaining the right capitalization and cost structures. Federal contractors, for example, regularly invest millions of dollars pursuing government sales opportunities that can require many months – even years – to close. If they close. When the stakes are that high, opportunities must undergo a thorough internal risk review before managers can decide whether to compete. One criteria: can the company afford to lose? Without a shared view of risk between Finance and Sales, more CXO’s would unwittingly bet the company. Many do.

Spreadhseet-facing Finance, and Customer-facing Sales – an odd organizational coupling, prone to bickering and personality conflicts. Yet, they must cooperate, because Finance and Sales grapple with the same uncertainties. Notably, how much will customers spend? When will they spend? and how likely are the answers to these two questions? The shared challenge of managing the risks should bring these two entities closer together. But that’s not always easy.

“Companies that embrace enterprise-wide risk management face the daunting task of instilling a risk awareness in a corporate culture focused on other objectives,” Barton, Shenkir, and Walker wrote in their book, Making Enterprise Risk Management Pay Off: How Leading Companies Implement Risk Management. An idea that some executives have put into practice. “To me, running a business is all about managing risk and managing returns, whether on the financial side or the balance sheet side, or running a field operation,” said Unocal CFO Tim Ling. Others agree. “Managers have to make a lot of day-to-day decisions without consulting the higher-ups. If they understand the financial parameters they’re working under, those decisions can be made more quickly and effectively. The company’s performance will be that much stronger,” Karen Berman and Joe Knight wrote in their book, Financial Intelligence.

Risk harmony between Finance and Sales means

1. Communicating the organization’s capacity (appetite) for risk. The CFO establishes this, and he or she is responsible for communicating to Sales which risks are acceptable, and which ones are not. Sales needs this information for its strategic and tactical planning.

2. Identifying and ranking revenue uncertainties based on frequency, probability, and consequence – a collaborative knowledge-sharing effort.

3. Developing strategies and tactics to support cash-flow requirements. Finance and sales must share knowledge about pipeline processes and velocity, sales compensation and incentives, lead qualification practices, and ethical sales governance.

4. Correcting inconsistencies. Companies get into trouble when Sales accepts more risk than the company can absorb, or avoids risks that the company requires to achieve its strategic goals. Similarly, Finance must develop risk mitigation strategies suited for the markets in which the company competes. Put another way, if you can’t run with the big dogs, stay on the porch.

Revenue volatility, the arch-enemy of cash flow planning, comes from risks that have come home to roost. CFO’s see the evidence in actual sales lines spiking and plummeting violently around their more graceful counterparts, planned revenue curves. Closer collaboration between Finance and Sales won’t eliminate the gaps, but it can reduce the area between planned and actual.

Most important, risk collaboration between Finance and Sales will help CFO’s better understand how close wrecking balls are to the cash flow plan, and which direction they are heading.

Accuracy! and Other Myths about Revenue Forecasting

Tuesday, 15 December 2015 15:41
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Most people don’t humble brag about revenue forecasts.

“Our #revenue #forecasts have been 2% off for 7 straight qtrs. Can’t make them accurate. #annoyed”

But some have honest anger.  When I look online for the phrase, bad sales forecasts, I receive around 2,300 results. Nothing better than a search box for discovering sensitive nerve endings.

The phrase, Forecasts suck, and its semantic siblings yield a cumulative 3,900 results. Other searches yield a trove of moaning, griping, and hand-wringing over “bad numbers.” Forecasting has a learning curve, but for many companies, the trajectory points south. Clairvoyance: it’s a tricky game.

But numbers aren’t intrinsically bad. The processes that produce them are. Charismatic consultants remind us of that daily with a tool, honed for shaming – a PowerPoint slide titled The Definition of Insanity.

No need to look up the definition’s originator, or the definition. It’s Einstein, and “doing the same thing over and over again and expecting different results.” The saying has been beaten to death. But allow me one more use, because this topic just screams out for it. Then, I’ll retire this bombastic finger-wagging admonishment from my writing forever. I promise.

Everyone, it seems, commits forecasting mistakes. Check your newsfeeds for daily updates. Some are monstrous: “Just this January, the Congressional Budget Office projected that enrollment [for coverage under the Affordable Care Act] would be 12 million for 2015. And a year ago, it had forecast 13 million . . . A little bit of math shows that sign-ups in 2015 came in 22% below the CBO’s earlier forecast,” according to Investors.com. Throwing fairy dust into the air would have been a better use of taxpayer money. Write your representative.

When forecasts miss, accusations swirl in the wake. “Our salespeople don’t have a clue.” “Our basic assumptions were way off.” “Marketing never anticipated that regulators could discover our emissions cheating . . .”

Such speculation gets fuel from five myths:

1. Above all, revenue forecasts must be accurate. “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 Bernstein wrote in his book, Against the Gods: The Remarkable Story of Risk.

2. Salespeople forecast unrealistic sales figures because they are “overly optimistic.” There’s no credible research that ties false optimism to salespeople any more than to lawyers, accountants, pilots, or programmers – though it’s hard to imagine hiring a sales candidate who says, “I have to think probabilistically about whether I can make goal.” So managers must accept their contribution to this problem. After all, they select people who demonstrate a rabid can-do attitude.

3. Only a leading-edge CRM solution makes more accurate sales forecasts possible. CRM systems are repositories for past events, but they have huge weaknesses for predicting the future. “Since we never know exactly what is going to happen tomorrow, it is easier to assume that the future will resemble the present than to admit that it may bring some unknown change,” Bernstein wrote. Others agree. “At their best, SFA/CRM systems give a comprehensive view of the pipeline, as well as detailed drill-downs on the state of play for any specific deal. Unfortunately, few CRM customers can really depend on (or even use) the forecast that the system produces. Most of the time, executives must second-guess the CRM data, making judgment calls that may not be consistent week-to-week and are rarely recorded anywhere. Worse, everyone’s first reflex is to call the rep if they need to find out what’s really going on with any account. As a result, the CRM data is seldom authoritative,” David Taber wrote in a 2012 article, Accurate Sales Forecasts and other CRM Fantasies.

4. Forecasts would be more accurate if salespeople were better at closing. Like many myths, this carries a shred of truth. Salespeople influence buying outcomes. But a good forecast model must account for what’s outside a salesperson’s control as much as it accounts for what’s within it. A forecasting system should include external forces and events that upend sales opportunities, such as new laws and regulations, personnel attrition, project delays, mergers and buyouts, changes in a prospect’s strategic objectives, supply chain disruptions, and fluctuations in international exchange rates.

5. If two or more people agree on a forecast outcome, their forecast is probably right. “Agreement among forecasters is not related to accuracy – and may reflect bias as much as anything else,” Nate Silver wrote in his book, The Signal and the Noise: Why So Many Predictions Fail – But Some Don’t.

People often flippantly use accuracy in conversations about forecasting. Here’s a clarification of the often-used terms:

Accurate forecast – predicted revenue equals actual revenue. An impossibly high standard. The goal of an accurate forecast is to eliminate variability.

Quality forecast – the forecast predicts [outcomes] well, with the available information, and according to specific objective and/or subjective criteria. The goal of a quality forecast is to reduce variability – not to eliminate it.

Valuable forecast – a forecast that facilitates better decisions. A forecast for recurring monthly revenue can be accurate when a customer has a contractual obligation for the purchase. But its value is not high.

I empathize with people who have a desire for accuracy. After all, variability is the arch-enemy of planners. We crave certainty and consistency. Why not? Orderly decision-making and predictability go hand-in-hand. Unfortunately, there are strong entropic forces in business decision making, which makes demanding forecast accuracy so unreasonable. “There’s no case in history where we’ve had a complex thing with lots of variables and lots of uncertainty, where people have been able to make econometric models or any complex models work,” forecaster Scott Armstrong told Nate Silver. “The more complex you make the model the worse the forecast gets.” Few can argue that a B2B business decision is linear and straightforward, especially ones that require collaboration, as most do.

“What’s the solution?” people ask me. “If we’re not after accuracy, then we should just give up with forecasting?” No. “The first action is to not ask for a forecast,” Ken Thoreson wrote in a blog, Why You Can’t Get an Accurate Forecast. He recommends asking for a revenue “commitment.” He makes a good point. If accurate forecasts are unattainable, quit hounding people for them, or quit griping when they’re wrong.

I believe planning works best when people concentrate on forecast quality, which continually seeks the combination of information that best predicts when revenue will be realized, and how much it will be. Most important, forecast quality doesn’t penalize the forecast provider for being wrong. That’s inevitable. Rather, it focuses on refining information so that variability can be reduced. One characteristic that distinguishes information from data is that information reduces uncertainty. And good information reduces uncertainty better than mediocre information.

The pursuit of forecast quality over accuracy represents a subtle, but critical shift in thinking. Forecast quality keeps high predictive value at the forefront. And it keeps The Definition of Insanity from being mentioned whenever forecast revenue and actual revenue don’t perfectly match.

Note: this column was featured on CustomerThink, November, 2015. To read the original column, please click here.

Revenue Planning 2016: Don’t Plop All Your Risks on Sales

Monday, 09 November 2015 14:59
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Four years ago, Martin Winterkorn, now the former CEO of Volkswagen, described an audacious goal to triple the company’s US sales. As he explained it, that achievement would be a milestone for toppling Toyota as the world’s largest automaker. “By 2018, we want to take our group to the very top of the global car industry,” he said.

In October, it was Winterkorn who was toppled as CEO when Volkswagen admitted to circumventing emissions rules. The company confirmed that software designed to fool regulators was installed in over 11 million diesel-powered vehicles. Deceit, too, can be mass produced.

But the idea behind VW’s strategy wasn’t original. It came from an ancient financial fact: transferring risks to others produces revenue and profit. Through clever software coding, VW saved billions of Euros in research and development, time-to-market, and the possibility that they might get bupkis for their effort. Health risks from dirty air? Deaths from emphysema and asthma? Those will be someone else’s problems. The VW Marketing team provided the right message: Clean Diesel. “Let’s face it: VW took advantage of a bunch of hippies with that line,” Dan Neil wrote in an article, VW Lost Its Moral Compass in Quest for Growth.

Winterkorn’s peripeteia reminds me of Yertle the Turtle, by Dr. Suess. King Yertle was a tyrant who conscripted his turtle underlings to place themselves in a stack so he and his throne could be higher than the moon. His project came to an end when the lowest turtle, Mack, burped, causing the pile to crash back to earth.

Then again, from below, in the great heavy stack,
Came a groan from that plain little turtle named Mack.
“Your Majesty, please . . . I don’t like to complain,
But down here below, we are feeling great pain.
I know up on top you are seeing great sights,
But down at the bottom we, too, should have rights.
We turtles can’t stand it. Our shells will all crack!
Besides, we need food. We are starving!” groaned Mack.

Presidential candidate Bernie Sanders can probably recite this dark rhyme in his sleep. It’s all about blind ambition, passion, and arrogance – a recurring, toxic C-suite trifecta, not limited to Volkswagen. “Shouldn’t a business manager care about whether capital is productively deployed to maximize returns, not about generating sales volume for its own sake?” Holman W. Jenkins, Jr. asked in The Wall Street Journal last week.

But many executives view selling risks the same as Winterkorn. They believe that sound financial strategy means dumping risks on others whenever possible. Sales workers toil under this ethos, bearing the brunt of business uncertainty. Employment-at-will. Compensation-at-risk. Flex scheduling. The Uberization of work. Orwellian-sounding terms routinely embedded in commercial parlance. “If this sales game is too much I’ll figure something else out,” a commenter, Mimii, wrote on Indeed.com in a forum titled, Things You Should Know about a Sales Position with AT&T Wireless.

Another commenter, Katie D, wrote “. . . since the last time I posted on here, AT&T changed the commission structure, which they do quite often. So yes, I am now working for peanuts and missing all my son’s football games . . .”

Not everyone in the conversation shared Katie D’s misery. But I couldn’t help thinking about her spirit as she tackles AT&T’s revenue goals. I envision her at the store, clad in a powder blue AT&T polo shirt, feigning a happy demeanor, while she longs to be part of her son’s fleeting childhood. Retail bosses and business bloggers call the Katie D’s of the world Customer-facing personnel, an appropriately tepid and joyless term.

“They have up to 48 hours in advance to change the schedule on you. So make sure you always check your time the night before so you don’t get a point for tardiness,” Katie D opined in another comment. Some would say she’s lucky to have a job. “Oh yeah, I used to be a salesman, it’s a tough racket.” The written rendition doesn’t come close to replicating Alec Baldwin’s mocking sarcasm in Glengarry Glen Ross.

Today, Mack from Yertle wears a tie and carries a mobile phone. And his belching can be heard all over social media:

“Hundreds of people are leaving [Oracle] each quarter,” a salesperson said in 2013, speaking on condition of anonymity. “Oracle has a horrible reputation in the tech sales circles at this point, so yes I see a migration from those who are competent, experienced, and see the writing on the wall,” another said, quoted in an article in Business Insider. “One issue frustrating salespeople is that they have been given quotas to sell Oracle hardware, even though they specialize in software, our sources tell us. That’s problematic because at many enterprises, the IT people who buy software are not the same people as the ones buying [hardware]. It’s an entirely different process.”

A salesperson from IBM shared a similar story:

“I was with IBM for 10 years and was the #1, #2, #1 rep in my software brand in the NATION for years 2009, 2010, 2011 respectively. In 2009 and 2010, I was paid accordingly. At least by IBM standards. In 2011, they screwed us all. 2012 was shaping up to be the same. In 2011, I was paid $40,000 commissions on $12,000,000 in revenue. Why? I was given a $12,000,000 quota. I left in February…and my former region’s best and brightest are peeling off.”

Why do companies shovel risk on employees, and then claw back their remuneration? Because the ka-ching is irresistible. And, because they can. Many employees simply put up with it. “I’ll take my chances with the added pressure of sales and high quotas if it means being able to provide for my daughter a bit better,” Mimii wrote in 2013. I don’t know whether she stuck it out, but the odds aren’t good. The employees “least committed to a company are its salespeople, 38 percent of whom planned to leave within two years.” A finding from a 2001 Hay Group Survey, titled The Retention Dilemma.

Variable compensation for salespeople offers many advantages, including higher pay, and lower risks for employers. But risks must be equitably shared. And they must be managed – not dumped elsewhere, like raw sewage into a river, or carbon into the atmosphere.

In 2016, there are seven imperatives for managing revenue risk:

1. Capturing, preserving, and sharing information. Quality information repositories have become the linchpin of selling. Yet, using a smokescreen called capital preservation, some organizations maintain antiquated systems that heighten selling risks. That’s changing. Companies currently spend approximately $23 billion each year on sales software, according to The Wall Street Journal, in an article, The Data-Driven Rebirth of a Salesman. “Sales offers possibly the biggest opportunity today in adding [artificial] intelligence in the enterprise,” said Mike Dauber, a partner with venture-capital firm Amplify Partners who has invested in the new generation of sales tools.

2. Acquiring, hiring, and retaining business development talent. “Talent acquisition and retention is a huge component of what we [CEO’s] need to think about,” said Christopher H. Franklin, CEO of Aqua America, Inc, a water utility in Bryn Mawr, PA. “That is where you get to set the culture.”

3. Ensuring high workforce productivity. The traditional numbers game mentality involves flogging salespeople for more revenue output. While that approach might provide positive short-term results, it sacrifices equipping salespeople with ways to be more productive. That means giving them proper tools, information, education, and professional development.

4. Continually matching sales resources to customer need. A sales process that doesn’t match buyer need jeopardizes revenue. Yet many companies fail to adapt, insisting that sales teams adhere to ineffective processes, or maintain ones that provide little value to customers.

5. Assigning, monitoring, and enforcing sales goals that create value for the company. Many organizations are short-sighted when developing sales goals, limiting them to revenue objectives. Executives overlook other opportunities for Sales to bring value, including high customer satisfaction, market intelligence, and higher profits.

6. Modeling and preserving high ethical standards. This needs no explanation as Volkswagen’s brand reputation implodes.

7. Increasing revenue opportunities. – A roll-up of all of these. Managing revenue risk requires getting better at growing sales. That includes expanding the number of accounts to call on, increasing win-rates, growing installed customer revenue, and reducing customer churn.

“Everyone knows that quotas will be going up next year . . . ” The predictable preamble to fourth-quarter sales meetings around the world. But will risks increase, too? I challenge anyone to find a Volkswagen salesperson who has been offered quota relief for the risks that Winterkorn shoved into the dealer channel.

Before I stomp on C-Level executives who blithely chuck their risks onto someone else – or in Volkwagen’s case, blast it out their tailpipes – I want to share a thought: transferring risks is as much a part of business as the exchange of goods and services. But management’s goal should be not only ensuring it’s done profitably, but openly, equitably, and legally.

This article originally was originally published on CustomerThink for Navigating Revenue Uncertainty. To view the original article, please click here.

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