Category Archives: Sales strategy

Revenue: MiMedx Shows How to Fake It Till You Make It

Suppose your company pioneered a product able to improve the health of millions of people. Suppose that over the past five years, you reported at least 50% year-to-year revenue growth. To cap it off, suppose Fortune recognized your company as the fifth-fastest growing public company in the US. How might your company’s revenue prospects appear to investors, and what would be the impact on its stock?

If you were prone to making understatements, you’d say the share price would increase. And that’s exactly what happened for MiMedx , a company that makes human skin grafts for surgical use, and whose market value once reached $2 billion. Then, in June, 2018, a load of financial poop went airborne, and traveled into the company’s twirling fan.

That’s when “the company said an internal investigation had shown that its reported financial results going back to 2012 were no longer reliable and would have to be restated,” according to a Wall Street Journal article, Highflying Medical Firm Falls to Earth, Its Sales Questioned (July 24, 2018). As of this writing (July 27), the market cap for MiMedx was under of $464 million. MiMedx’s president, Parker “Pete” Petit has resigned, and an interim executive now runs the company. His specialty: “restructuring troubled businesses.” I’m reminded of Icarus, yet again. Those ancient Greeks – they sure understood human foibles. Somehow, they did it without the benefit of social media, AI, predictive analytics, and all. Amazing.

Stories about companies that tanked after achieving soaring revenue seem commonplace. Often, it’s the result of scrappy competitors who saw an opportunity, and seized a cash cow that a company was contentedly milking. Sometimes, it’s the result of self-satisfied, complacent management, who paid little heed to oncoming trains that demolished their business strategy. “We’re going to get flattened? . . . I thought you said ‘fattened!’”

MiMedx suffered from none of these mistakes, and that’s part of the tragedy. “No one has suggested that MiMedx’s products are faulty,” the Journal says. According to a company statement, “[MiMedx] is operating its business as usual as it continues to grow, invest in its product pipeline, and focus on serving healthcare providers and their patients.”

“Business as usual.” A sound bite that analysts, customers, and prospective employees sometimes like to hear. But it turns out that there was a bit of revenue hanky-panky going on.

Well, a lot of hanky-panky – if the allegations are true. “A Wall Street Journal review of company emails, court documents and internal complaints, plus interviews with current and former employees paint a picture of a company seeking to grow at almost any cost.” Where have I heard this before? Sounds so familiar . . . Bells Cargo? . . . Fells Wargo? Help me out . . .

In the Wall Street Journal article, employees describe a potpourri of revenue inflation tactics. I can’t call them innovative – some have been around for decades – but what makes MiMedx especially disturbing is what happened to employees who blew the whistle. Among the techniques former employees described in The Wall Street Journal article:

  1. Channel stuffing. “MiMedx sometimes shipped more skin grafts than had been ordered, and booked them as sales . . . MiMedx sales records show the company recorded a shipment of 135 oversized skin grafts to a Las Vegas plastic surgeon’s office, which former employees said is way beyond the 10 or so smaller pieces in a typical physician order. The shipment was recorded at 8:00 pm on September 29, 2016, just before the end of a quarter. No one in the surgeon’s office had ordered the goods, according to a former employee of the office.””
  2. Browbeating the sales force. “What else can u ship by end of month?” read one message to a rep, which continued, “Need all u can put in today up to $100k if possible.”
  3. Booking consignment inventory shipments as sales. “Several former employees said that at times, near the end of a quarter, the company would book as sales some of the goods sent to hospitals on consignment but not yet used.”
  4. Mislabeling products for medical uses that receive higher reimbursement from insurance companies.
  5. Providing advisory services to physicians on how to maximize reimbursement for the company’s products.

Customers have the unfortunate habit of directing their ire about bad selling behavior toward salespeople. I understand. The front-line rep is a conspicuous target. Most customers never meet the Sales VP who hatched an incentive plan that encourages revenue production over anything else. They don’t hobnob with the VP of Human Resources who carries out heavy-handed sales management policies, especially the punitive firing part. If they did, they’d learn about the high-pressure manipulation under which salespeople work, and how that penetrates their customer conversations. They would understand that the objectionable behaviors salespeople display are almost always result from what management encourages, and ultimately, what employers pay salespeople to do.

But many salespeople are principled and resist adopting practices that compromise their morals and ethics. Or, violate the law.  But for some, pushback comes at a cost.  With MiMedx and Wells Fargo, management concocted penalties to ensure employees kept quiet, which allowed their devious machinery to continue operating. Both companies eventually poisoned themselves. Time will tell whether the dosage was lethal.

It would be easy to attribute the transgressions at MiMedx to good old fashioned greed, and leave it at that. Why attempt to fix what you can’t change?

But MiMedx illustrates a preventable problem. Four root causes:

  1. Flawed proxies. In the case of MiMedX, the flawed proxy was revenue growth, which investors often confuse as a sign that other things they covet are present: talented management making smart decisions, fast-growing industry or market, killer business strategy, great products, rapid customer adoption, loyal repeat customers. MiMedX demonstrates that revenue is a weak proxy because a growing company can be infected with problems, and revenue is easy to spoof.
  2. Misplaced and outsized financial rewards. As with Wells Fargo, when executive compensation plans put heavy emphasis on stock price increases, nobody needs to guess how managers will direct their energies.
  3. Ethics absent from corporate culture. Tom Tierney, a former MiMedx Regional Sales Director, described the company’s culture as “a mind-boggling level of sales and accounting irregularities,” which he characterized as a “win at all cost” company culture.
  4. Lack of safety for employees when reporting fraud and abuse. “MiMedx provided employees with a way to report issues that troubled them. Eight ex-employees said they were fired after they spoke up,” according to The Wall Street Journal.

There are plenty of sound reasons to pursue rapid revenue or market share growth. For companies that are first to market with an innovation, rapid revenue growth enables them to establish platform or production standards for an industry. It helps them build economies of scale, which raises barriers to entry. It gives them bragging rights as the market leader. All of these have positive strategic consequences. With MiMedx, the quest for rapid revenue growth appears to have backfired because its primary purpose became apparent: to line the pockets of the company’s owners.

I blame analysts and investors. We have better, deeper metrics than revenue growth to assess the future vitality of a company. It’s time to start trusting those numbers, because as we’ve learned by now, revenue is wicked-easy to fake.

Three Reasons Sales Forecasts Don’t Match Results

“Our sales results never match what’s forecast!” As the saying goes, “if I received a dollar every time I heard this complaint, I’d be contentedly fly fishing in a remote river right now, untethered from the grid.”

Inflated expectations? First, we need to understand what match means in the context of forecasting. If match means equals – as some people believe – we only need one reason: because it’s a forecast. Trying to get sales forecasts to hit actual revenue bang-on is a fool’s errand.

And accuracy might not be as valuable as you think. If I have a customer who reliably places an order for 100 units every month, I can forecast that amount, and – assuming the order is received – my forecast will be 100% accurate. Strange as it sounds, a lot of purchasing is just that way: steady, predictable, consistent.  What is the value of that forecast to my company? Minimal, because they already know it’s coming and they have planned production, personnel, and materials accordingly.

Accurate as it is, there’s little value in my forecast because there’s no intelligence behind it, and little possibility of variability. If you and I are standing in the middle of a nascent hurricane, would there be value to you if I said, “over the next 24 hours, we’re going to experience heavy rain.”? I’d be accurate as all get out, but my statement wouldn’t be particularly valuable. Yet, companies encourage salespeople and their managers to indulge in similar forecast gaming by penalizing them for “inaccurate” forecasts, and rewarding them for playing things safe, and predicting revenue only when it’s solidly assured. This discourages probabilistic thinking and situational awareness – two essential competencies for salespeople today. And vital for planners.

On the other hand, if match means in the ballpark, then companies need to specify what that means in terms of variance, because an acceptable variance for one company might not be acceptable for another. And acceptable variance might change for a given company, depending on market conditions and other forces.

In sales, there are three reasons for forecast variances (defined as the delta between expected results and actual, usually in terms of revenue or unit volume):

  1. Sales forecasts are projections dependent on human decisions, which are exceedingly difficult to predict. That’s true with just one decision maker. And when there are multiple decision makers – for example, with buyer committees or additional levels of approval – forecast complexity skyrockets, often defying intuition and mathematical prediction.
  2. [Stuff] happens – though most sales managers are loathe to admit it. Across a broad spectrum of situations, unanticipated events occur with such frequency that there is vernacular for them: Black Swans. In forecasting, salespeople and their managers seldom allow for them, and they include such things as supply chain interruptions, buyouts, executive defections, sudden strategy changes, and reallocation of project funding.  These are frequently catastrophic deal-killing events, and they are out of the salesperson’s control. Every forecast must consider these possibilities and more, and account for them.
  3. Senior management injects biases. Sales managers commonly demand that their reps carry “healthy” revenue pipelines, and they stigmatize their reps as “low performers” if they don’t project revenue that’s congruent with quota. The result: forecast candor is systemically discouraged, while forecast inflation gets rewarded with a pat on the back.

Sales VP’s often tell me that forecast variances result from sales reps who are “overly-optimistic.” That’s often partly to blame. Optimism can cloud situational awareness, which creates volatility – the bane of CFO’s and production planners. But there are many other risks that come into play, and it’s incumbent on managers to know what they are.

My next article will cover what makes a sales forecast high quality.

Skepticism: An Antidote for Statistical Malpractice

Michael Shermer, founder of the Skeptics Society, doesn’t suffer fools. He questions assertions that others accept as fact. He challenges claims of “scientifically proven” when he doesn’t see any science. He examines experimental hypotheses, and weighs research methods and data. “The principle is to start off skeptical and be open-minded enough to change your mind if the evidence is overwhelming, but the burden of proof is on the person making the claim,” he says, adding, “I would change my mind about Bigfoot if you showed me an actual body, not a guy in an ape suit in a blurry photograph.” [emphasis, mine]

Just like those grainy images of Bigfoot, marketers often use shaky evidence to support contrivances of irrefutable proof. They crow that numbers don’t lie, and latch onto statistical tidbits to drive home their points. “Studies show . . .” The cliché preamble to a sales pitch.

“Hands down, the two most dangerous words in the English language today are ‘studies show,’” Andy Kessler wrote in a Wall Street Journal editorial, Studies are Usually Bunk, Study Shows (August 13, 2017), “If a conclusion sounds wrong to you, you’re probably not a hung-over grad student.” Snarky, but I get his point. Heavy partiers make poor skeptics. What about the rest of us?

Marketers routinely spin study percentages into clickbait. A Frinstance: 39 Shocking Sales Stats that Will Change the Way You Sell, from which I drew this sampling:

  • Email marketing has 2x higher ROI than cold calling.
  • 92% of all customer interactions happen on the phone.
  • 92% of salespeople give up after four “no’s”, but 80% of prospects say “no” four times before they say “yes”.
  • 44% of salespeople give up after one follow-up call.
  • 68% of companies struggle with lead generation.
  • 50% of sales time is wasted on unproductive prospecting.

The article gives separate sources for each of these nuggets, but from there, tracing their provenance becomes convoluted.

No matter. Many stats get bandied without scrutiny. They’re embedded in tweets that are liked and re-tweeted. The shares are shared, and those shares get re-shared. And on, and on. Along the way, the original meanings of many numbers get warped or over-amplified. Flawed findings mutate into hallowed truths. As these clipped numerical snapshots flow through the social media pipeline, they lose meaning, and transform into verbal nothingness: “44% of salespeople give up after one follow up call.” Since I don’t know the research definition of give up, how it was measured, or the operational meaning of a follow up call, it’s impossible to draw any insight from this statement. But the person who shared it in this article has a goal, which is to change the way I sell.

“There’s some kind of weird thing that happens to people when mathematical scores are trotted out. They just start closing their eyes and believing it because it’s math,” says Cathy O’Neil, author of the book, Weapons of Math Destruction. Statistics persuade. That’s often the point of using them. They can give authoritative glamor to sales pitches. They can also be used for malevolent purposes, like distracting prospects from seeing truth, as Coca Cola recently demonstrated.

Coca Cola funded faux research through the now-defunct Global Energy Balance Network (GEBN). The objective was to promote the falsehood that preventing obesity didn’t depend on people eating less, or (most importantly) drinking less soda. Instead, the wonks at GEBM told us that people just need to be more active. A message Coke knew that people wanted to hear, and advanced their revenue objectives at the same time: Getting thin didn’t mean anyone needed to give up their habit of swilling a 40-ounce Big Gulp.

Try this out: In a search window, type, “% of marketing content goes unused by sales” – quotes and all. Just now, my top three results (out of 3,150) are “80%,” “70%,” and “60%” respectively. Further down the stack I see “90%.” If you’re not sure what to believe, you’re in good company. Still, I get a strong vibe: content sucks. And not just content in general, but my content.

The not-subliminal message: “Be really, really dissatisfied with your content strategy, and remember, we content gurus can fix it!” Expectedly, with every link, I found a company with a product or service to dig prospects out of a rut they probably didn’t even know existed.

Jordan Ellenberg, author of the book How Not to Be Wrong, refers to the practice of hyping stand-alone percentages as statistical malpractice. By cherry-picking a study’s percentage or finding and stripping away its context, additional results, ancillary data, explanatory detail, and caveats, its meaning becomes corrupted. In this way, instead of imparting understanding and knowledge, statistics serve as mathematical bling to trick out a marketing message.

Unless you are skeptical, you’ll miss the flip side of these percentages, which conveys a different reality. Based on the percentages from my original query, anywhere between 10% to 40% of content is used by sales. Marketing teams create content for many different purposes, and looked at this way, the statistic (whichever one you choose to believe – 60%, 70, 80, or 90) seems less dire. Further, content creation is innovation, and when compared to another measure of innovation efficiency, for example, the 85% failure rate of new consumer product introduction, these numbers become less alarming. Relief! Perhaps you can wait another year before hiring an intern to spiff up your company’s content.

Guidelines for the aspiring healthy skeptic. James Loewen, author of Lies My Teacher Told Me,  recommends questions for vetting history textbooks. I’ve adapted his points for marketing and sales:

  1. Why was the study conducted?
  2. Why were the measurements chosen? Which ones weren’t – and why?
  3. In presenting the findings, whose viewpoint is reflected – and whose was omitted?
  4. Do the points of the study/article cohere? Are they logical? Are they believable? What explains the anomalies?
  5. Are the findings corroborated elsewhere?

Many biz-dev articles I read decompose rapidly when tested on numbers 4 and 5. If the “Top 3 success traits in a sales person are [X], [Y], and [Z],” what explains salespeople who are successful despite having a completely different trio of characteristics? And I’ll wager that another study of customer interactions could be conducted using a different sample, yielding a substantially different result from “92% of them happen on the phone.” All too often, those sharing such information are happy to reply to accolades posted on their articles, but don’t respond when pressed for more detail or clarification. I’m assuming they’d rather not be bothered.

According to Andy Kessler, “Many of the studies quoted in newspaper articles and pop-psychology books are one-offs anyway. In August 2015, the Center for Open Science published a study in which 270 researchers spent four years trying to reproduce 100 leading psychology experiments. They successfully replicated only 39 . . . Add to this a Nature survey of 1,576 scientists published last year. ‘More than 70% of researchers have tried and failed to reproduce another scientist’s experiments,” the survey report concludes. ‘And more than half have failed to reproduce their own experiments.’” If we chose to be similarly introspective in marketing and sales, our performance would likely not fare any better.

I’m under no delusions that my squeaky complaining will slow the tsunami of statistical malpractice. But if asking these pointed questions causes anyone to pause before hitting the Retweet button, or to hesitate before chiming “spot on!” following a study gratuitously calling itself authoritative, then mission accomplished.

Daniel Levitin, author of A Field Guide to Lies,  provides a counterpoint to hyped statistics, one that underscores that the burden of proof must always be on the person making the claim:

“Statistics, because they are numbers, appear to us to be cold, hard facts. It seems that they represent facts given to us by nature and it’s just a matter of finding them. But it’s important to remember that people gather statistics. People choose what to count, how to go about counting, which of the resulting numbers they will share with us, and which words they will use to describe and interpret those numbers. Statistics are not facts. They are interpretations. And your interpretation may be just as good as, or better than, that of the person reporting them to you.”

What makes statistical malpractice insidious isn’t that percentages are purposefully shocking. It’s that the numbers are actually fairly ordinary, and pander to our biases. Everyone has experienced a salesperson who is slovenly or unmotivated. It’s not a stretch to believe a “finding” that 40% of them give up a customer pursuit after perfunctorily following up. Effective time management plagues nearly everyone. Who would be astonished to learn that 50% of sales time is wasted on unproductive prospecting? This is the “secret sauce” in statistical persuasion: find a bias, and harden it with a number. Never mind that terminology like give up, struggle, and unproductive are too fuzzy to have meaning in an experimental sense.

Grainy images, be damned. No matter what, people still really want to see Bigfoot.

Companies That Abuse Privacy Might Feel Consumer Fury – Again

The company Ashley Madison offers an audacious capability: extramarital affairs.  “Ashley Madison is the most famous name in infidelity and married dating,” proclaimed the company’s marketing pitch in 2015. “Have an Affair today on Ashley Madison. Thousands of cheating wives and cheating husbands signup everyday [sic] looking for an affair . . . With Our affair guarantee package we guarantee you will find the perfect affair partner.”

A great value prop for those seeking such experiences – until July of that year, when hackers broke into the company’s data files.  The thieves coined a name for themselves, The Impact Team. A modest appellation, considering the extensive collateral damage their activities produced.

Mission accomplished. The Impact Team’s cyber-haul included 25 gigabytes of profiles describing the people who signed up for Ashley Madison’s services. Many records included email addresses ending with .gov and .mil (the domain extensions for the US government and Department of Defense, respectively), which stoked curiosity, to put it mildly. Had the hackers compromised the US nuclear launch codes, there would have been less panic in Washington.

But unlike most hackers, The Impact Team was motivated by more than extracting ransom. Impact Team ostensibly wanted to preserve morality, citing that the reason for the hacking was Ashley Madison’s facilitation of marital infidelity. Another website, EstablishedMen, was also targeted. Both are owed by parent company Avid Life Media (ALM), which rebranded as Rubylife in July, 2016. “Too bad for those men, they’re cheating dirtbags [sic] and deserve no such discretion,” the hackers wrote. The Impact Team threatened to expose the identities of Ashley Madison’s customers if ALM did not shut down the websites.

There was more. The hackers complained that although ALM charged users $19 to delete personal data from the Ashley Madison website, the company did not fulfill its promise – not fully, anyway. Instead, ALM simply relocated the “deleted” records to its backend servers. “Too bad for ALM, you promised secrecy but didn’t deliver,” the hackers said. Clearly, the hackers feel that philanderers deserve honest treatment from vendors.

Despite getting caught with their cyber-drawers down, “Avid Life Media defiantly ignored the warnings and kept both sites online [Ashley Madison and EstablishedMen] after the breach, promising customers that it had increased the security of its networks. That wouldn’t matter for the customers whose data had already been taken. Any increased security would be too little too late for them. Now [those customers] face the greatest fallout from the breach: public embarrassment, the wrath of angry partners who may have been victims of their cheating, possible blackmail and potential fraud from anyone who may now use the personal data and bank card information exposed in the data dump,” according to a story in Wired Magazine published shortly after the incident (Hackers Finally Post Stolen Ashley Madison Data, August 18, 2015).

The Ashley Madison hacking was not the first incident involving a vendor that failed to adequately protect customer information from hackers. There was TJX, parent company of retailer TJ Maxx in 2003 (94 million stolen records), Sony PSN in 2011 (77 million), Target Stores in 2013 (70 million), Home Depot in 2014 (56 million), and eBay in 2014 (145 million). In fact, of The Nine Biggest Data Breaches of All Time (Huffington Post, August 20, 2015), Ashley Madison doesn’t even make the list.

But if someone maintained a list titled Most Awful, Ashley Madison would rise to the top. Ashley Madison scared the bleep out of everyone because the incident compromised not only financial information, but lifestyle preferences – the kind an individual would not likely share with friends or family. Purloined credit card numbers can be deactivated, but evidence of promiscuity and related information, well, once liberated, those horses aren’t heading back to the barn.

Should companies care about protecting personal customer information? The question is not rhetorical. By being opaque with customers about what they were doing with their sensitive data, Ashley Madison apparently didn’t care enough. Some could say they didn’t care at all. And their cyber-barriers weren’t insurmountable for the dedicated hackers on The Impact Team. Post-Ashley Madison, people began to think about their information in the IT cloud, and the associated risks to personal privacy. “Click to submit!” – software developers have made sharing personal data all too easy.

People worried about where their private information goes, where it’s stored, and who might have access to it. They began to imagine voyeurs who might crave such information, and they wondered what criminals could do with it. Consumers realized they couldn’t entrust their privacy to firewalls, encryption, secure data storage, and other jargony techno-obfuscations that marketers routinely use to sweeten their “privacy assurances.” Poignantly, Ashley Madison meant that most consumers did not need any imagination to understand the outcomes when vendors are lackadaisical about data governance.

Customer worry becomes a marketing worry. If customers can’t trust that their privacy won’t be abused, they won’t trust the many mechanisms that happen in online commerce, notably, allowing their primary information and data exhaust  to be collected, stored, and analyzed. If – when – that happens, marketers will experience a setback in solving a perennial problem: Finding the likeliest buyers. Right now, marketers depend on both to fuel their ravenous lead-generation engines, and to close transactions. With every data hacking, regulators raise their hackles, and customers become ever warier. “Hell hath no fury like a woman scorned!” The same for customers when their trust and privacy are abused.

Fury – aka The Do Not Call Registry. In the ’80’s and ’90’s marketers got increasing blowback from agonized customers who felt their privacy had been violated, a development that directly contributed to the US Federal Trade Commission establishing the Do Not Call Registry in 2003. The registry’s intention was to curtail what became a reviled business practice: marketers using telephone contact to prospect for new business. Many telemarketing calls were made to residences, and numbers-driven marketers didn’t care about customer experience, often prescribing the calls to occur at dinner time, when prospects were more likely to be home.

Telemarketing began with the advent of the telephone, according to Wikipedia. It flourished in the 1970’s, when marketers got savvier about effective tactics, which were widely shared as “best practices.” That was the beginning of its demise.

The primary customer data needed was culled from lists of residential phone numbers, and ZIP Code directories, all available to the public. For marketers, the telemarketing sales channel became stupid-easy to switch on, and – this is crucial –  wicked-hard for customers to avoid. Before caller-id and call blocking, the only choice for a customer when a telemarketer called was to not answer the phone, and wonder whether they had just missed something important. Vendors became addicted to the low costs and revenue results. For senior executives, self-regulating one’s cash cow did not have wide appeal.

Yet, Do Not Call was a bellwether in the customer fight for privacy, and it caught on like wildfire. While today, it appears that Do Not Call doesn’t have sufficient penal claws to deter vendors from flouting its provisions (my home regularly receives numerous daily phone solicitations, despite being on the registry), its symbolic message is stunning.  Today, there are 217 million numbers on the list. Since its inception, that averages to 42,465 numbers added per day for 14 years. I consider that an “opt-in” success story that should make any CMO drool with envy, albeit for the wrong reasons. The message to marketers: “Do not intrude on my privacy. Do not abuse my personal information. Because if you do, you’ll lose your privilege. Sincerely, Your Customers.”

When it comes to privacy, marketers have no scruples. None. COPPA, The Children’s Online Privacy Protection Act was enacted to prohibit the collection and use of personal data from children under 13 years old. But there’s a problem: “More than 50 percent of Google Play apps targeted at children under 13 – we examined more than 5,000 of the most popular (many of which have been downloaded millions of times) – appear to be failing to protect data,” writes Serge Egelman, research director of the Usable Security & Privacy group at the International Computer Science Institute, in a Washington Post article, We tested apps for kids. Half failed to protect their data (August 7, 2017).  For example, when parents download an app from Google’s Designed for Families section in the Google Play store, they assume data about their child (or children) remains safe. Turns out, that’s a bad assumption.

Which kid-generated data is compromised? Device serial numbers (which are often associated with location data), email addresses, and other “personally identifiable information,” according to Egelman, who wrote that his company found such data had been transmitted to third-party advertisers, and that the nature of the data meant that those companies could engage in long-term tracking of these children.Fortunately, Egelman has developed a website for parents to check the “privacy behaviors of the apps” his company has automatically tested. Just when we thought it was safe to allow our children to stay inside and play on the computer . . .

Personal privacy: why ongoing consumer trust isn’t assured. “Today your data can be of four kinds: data you share with everyone, data you share with friends and coworkers, data you share with various companies (wittingly or not), and data you don’t share,” writes Pedro Domingos in his book, The Master Algorithm. As consumers, we’re betting that as companies like Facebook, Amazon, and others gain more data, their learning algorithms improve, returning more value to us. But Domingos says that the “problem is that Facebook is also free to do things with the data and the models that are not in your interest, and you have no way to stop it.”

“When we say we’ll protect your data, you must believe us! . . or not.” Today’s marketers extoll privacy in their customer messaging. After all, they smell money. “Onavo Protect for Android helps you take charge of how you use mobile data and protect your personal info. Get smart notifications when your apps use lots of data and secure your personal details,” the copy on Onavo’s website assures us. But Facebook, which spent $150 million to acquire Onavo four years ago, hasn’t been fully transparent what it does with the data. One thing is certain: Facebook didn’t plunk down $150 million because they fancied the name Onavo. “Facebook is able to glean detailed insights about what consumers are doing when they are not using the social network’s family of apps, which includes Facebook, Messenger, WhatsApp and Instagram,” according to an article in The Washington Post, Facebook’s Affinity for Copying Seen as Stifling Innovation (August 11, 2017) . How private is the data? Will Facebook use it for benign purposes? Will customers experience harm? I don’t know, and the answers aren’t provided in corporate fine print and written disclaimers.

In another example, this year Princess Cruises announced its Ocean Medallion bracelet that promises passengers a unique personalized travel experience:

“It’s cruise planner meets concierge — a guide that you can access everywhere — on touchscreens throughout the ship, your stateroom TV and your own mobile devices. Ocean Compass helps you navigate your ship and your cruise, like streamlining the boarding process, personalized shore excursions invitations, ordering your favorite drink and more . . . Upload your documentation and set your preferences ahead of time so you can swiftly walk on board and communicate everything your ship needs to know about you.”

And:

“Customize your personal Ocean Tagalong™ by body shape, color, pattern and marks (like tattoos) to best reflect your “alter ego”. This responsive digital companion follows you from initial registration to the end of your cruise (as well as rejoin you on future cruises). You’ll find it online within your profile, during interactive PlayOcean games like Tagalong Sprint, as well as through Ocean Portals found onboard Medallion Class ships. Tagalongs even evolve throughout the cruise, reflecting your unique personality and interactions, and will collect ‘charms’ that show off your achievements.”

To me, Ocean Medallion is a marketing name for sophisticated surveillance technology, and there’s “Ewwwwwwwwww!” by the bucket load throughout this cheery write up. Clearly, I’m not the type of customer Princess wants to reach, and I’m sure they’ve heard similar sentiments from others. They’re looking for a much different prospect. One who absolutely, positively cannot stand to separate from technology. Not even for a minute. I can distill Princess’s prose into a single sentence: “We know much about you even before you begin your vacation, and we track you from the time you come aboard, until the time you disembark.”

Where does Ocean Mediallion’s digital information go, who sees it, who uses it, and for what purposes? That’s not spelled out anywhere I looked on the company’s website, though I have little doubt that they have PhD data scientists who know. And it’s not reassuring that Carnival hasn’t updated their privacy policy since December 5, 2014, according to its privacy policy page. Just finding that out required a circuitous content journey. Good thing I liked the photos.

In today’s digital era, batches of delicate personal customer information are produced, captured, selected, sub-selected, curated, sorted, stored, compiled, combined, listed, cut, “value-added,” repackaged, warehoused, transmitted, sold, and shared, like rail cars of soybeans. Your data, e-shot, helter-skelter to the world! A massive logistics system operating in subterfuge, trafficking the data minutia of a human being’s existence, one individual at a time. Without industry self-enforcement, strong governance policies, and legal restrictions, tell me there’s not another Ashley Madison-type wreck about to happen, or already underway.

There’s an entrepreneurial opportunity here, in case anyone wants to step in. Pedro Domingos suggested one in how he envisions a new business model for privacy protection:

“The kind of company I’m envisaging would do several things in return for a subscription fee. It would anonymize your online interactions, routing them through its servers and aggregating them with its other users’. It would store all the data from your life in one place – down to hour 24/7 Google Glass video stream, if you ever get one. It would learn a complete model of you and your world and continually update it. And it would use the model on your behalf, always doing exactly what you would, to the best of the model’s ability. The company’s basic commitment to you is that your data and your model will never be used against your interests. Such a guarantee can never be foolproof – you yourself are not guaranteed to never do anything against your interests, after all. But the company’s life would depend on it as much as a bank’s depends on the guarantee that it won’t lose your money, so you should be able to trust it as much as you would trust your bank.”

I wonder whether a company can honestly commit to never acting against a customer’s interests, when those interests inevitably change. Still, I like his entrepreneurial vision.  In the meantime, Domingos asks, “Who should you share your data with? That’s perhaps the most important question of the twenty-first century.”

Author’s note: This article is the second in a series about consumer privacy. You can read the first article, In the Digital Revolution, Customers Have Nothing to Lose But Their Privacy by clicking here. In an upcoming article, I’ll outline important keys for corporate data governance.