Category Archives: Sales strategy

Close and Pay: How Marketing and Sales Freelancing Will Reshape Business Development

It’s 2025. You and a friend are sitting in a coffee shop, discussing an entrepreneurial idea you’ve been hatching. It’s a service for recovering excavated asphalt from crumbling roadways, shipping the material to refineries in undisclosed locations, and converting the whole mess into oil. Green Fracking. It became a thing in 2024, and you’re at the vanguard of the movement, ready to pounce on the hefty pot of gold that awaits. Oh, I’ll mention that crude now sells for over $800 per barrel, and the average price for a gallon of regular gas in the US just topped $12.46.

VC’s have been calling you day and night. You’ve muted your ringtone. Over lattes, you share details about your plan, and your friend is so excited that she convinces you ramp up sales right now. “With an idea this hot, we need to press on the accelerator – hard!” she tells you. She touches a few buttons on a mobile computing device attached to her wrist, waits a minute, and says “Launch sales,” loudly and slowly. She stares at the tiny display for about 15 seconds, turns to you and says, “Done! I have a global team of 38 business developers in place right now. Ready to start.”

Then, on an electronic tabletop screen, she deftly swipes her fingers in a wavy pattern known only to her, instantaneously gathering live video feeds of 38 different faces. Mostly young, but a few clearly over 40. Every race and ethnicity. An even distribution of men and women, along with several who appear androgynous. “Everyone’s here. Let’s go over the rollout,” she declares.

You haven’t yet named your company, but you remain calm. Back in 2015, her request would have put you on the spot. Now, you’re prepared. When you first sat down to talk with your friend, another app listened to your conversation, and mined it for key ideas, facts, and figures. It pumped that content into a template collaboration session, translated it into eleven languages, and created a nifty custom logo. Each newly-minted team member now has the rollout plan in front of them. From concept to coin in less than 20 minutes. Let’s go team! It’s showtime!

With ubiquitous IT connectivity, social networks, and streaming video, this vignette seems pleasingly within our grasp. Ten years from now, we’ll look back on today’s labyrinthine, un-agile biz-dev staffing process as a strategy killer. “All that recruiting, hiring, training, onboarding, developing, administering, and firing. What a quagmire! It’s a wonder any company ever got launched!” Thank goodness software applications have matured so we can bypass the miserable headaches associated with that getting the right people on the bus. But there’s one more component that contributes to this vision. A voluminous and mighty repository, without which, there would be no story, and no storytelling: freelancers.

Freelancing has permeated almost every type of business – from the prosaic to the sophisticated. From basic construction to biotech. Freelancers do most anything that needs doing – including marketing and sales. One freelance sales group on LinkedIn describes their purpose as “to develop network between Business Development Managers and Freelance Sales professionals. Sales professional can publish their sales opportunity as a Job where Business Development Managers can start discussing about the opportunity. Once scope is clear, both parties can talk to each other and Business Development Manager can buy the opportunity from the Sales professional on agreed price. Payment can be made once contract is signed for the opportunity [sic].”

Who needs a mercurial, difficult-to-manage sales force when you can just go to an exchange and buy a golden lead that another person has thoughtfully chucked over the fence? And if you’re a freelance salesperson, I’m sure you can earn a nice commission – assuming the deal closes, and you can wait long enough. Oh, I nearly forgot: the checks have to clear, too. The LinkedIn group, Freelance IT Sales Professional and Business Development Manager, began in 2009, now has almost 36,000 members. I contacted the group’s manager, Dinesh Singh, and asked if he had a handle on how much revenue was flowing through this exchange. He replied that he does not track it.

But other exchanges do. Tongal, a site for creative freelancers, has developed a network of 40,000 video makers. “Limitless creativity for businesses and people who need it. For our clients, the Tongal platform and community offer a constantly renewed and re-energized creative resource,” the company’s website tells us. Talent, just one mouse click away. Through Tongal, Colgate-Palmolive offered to pay any person who created the best 30-second advertisement for the Internet. The spot they selected was so good that Colgate-Palmolive decided to air it on the Super Bowl. The Super Bowl! Their cost for producing the ad? $17,000 – the amount awarded in the contest. (“The average Super Bowl spot has a production cost that’s north of $1 million and, based on how extravagant the concept is, some can easily double or triple this price,” according to Forbes.)

“Perhaps the most striking of all the on-demand [freelance] services is Amazon’s Mechanical Turk, which allows customers to post any ‘human intelligence task,’ from flagging objectionable content on websites to composing text messages; workers on the site choose what to do according to task and price. The set-up uses to the full most of the capabilities and advantages that make on-demand business models attractive: no need for offices; no full-time contract employees; the clever use of computers to re-package one set of people’s needs into another set of people’s tasks; and an ability to access spare time and spare cognitive capacity all across the world,” according to an article in The Economist, There’s an App for That (January 3, 2015).

Amazon’s sales pitch for Mechanical Turk makes an appeal directed to our innate sense of debits and credits: “For businesses and entrepreneurs who want tasks completed, the Amazon Mechanical Turk service solves the problem of accessing a vast network of human intelligence with the efficiencies and cost-effectiveness of computers. Oftentimes people do not move forward with certain projects because the cost to establish a network of skilled workers to do the work outweighs the value of completing it. By turning the fixed costs into variable costs that scale with their needs, the Amazon Mechanical Turk web service eliminates this barrier and allows projects to be completed that before were not economical.”

Another freelance exchange, Elance-oDesk, touts over 2 million businesses seeking 2,500 different skills from over 8 million freelancers, including 344,900 programmers, 43,600 mobile developers, 261,500 designers, 391,300 writers, and 83,900 marketers, from over 180 countries. The service recorded over $750 million generated in 2013. Eight million freelancers: just shy of the 2013 population estimate of the third-largest US metropolitan statistical area, Chicago-Naperville-Elgin Illinois.

Freelance workers will fundamentally change how business is conducted. Those changes will be reflected in corporate strategies, and will re-shape how people collaborate and interact. Monolithic infrastructures will melt away. So will fluffy corporate mottos like “our people are our greatest asset!” Which people? Your freelance team, which is to say, everyone you’re paying? “Our freelancers are our greatest asset!” . . . . Nah.

These anecdotes offer exciting glimpses into what makes freelancing so seductive for many companies. Now, anyone with a checking account has the ability to quickly obtain top talent at market rates without any long-term commitments. What’s not to love? Here, the most useful caution is to be very, very careful about what you wish for, because you just might get it.

With freelancing now gaining widespread use within many organizations, you can expect:

1. More automation. Freelancers and the people who seek their services will be matched up through sophisticated information technology and complex algorithms.

2. Hyper-specialization and further division of labor. Look for freelance workers who have honed one or two talents especially well. Blog writers who know little about PR. Graphics designers who know little about web development. Lead-generation specialists who have never “closed” a sale.

3. More routinized tasks. Freelancers who are paid by the hour, or who are paid for results, will eschew tackling projects work that requires them to vary from their profitable “core competencies.”

4. Decreased emphasis on understanding “the big picture.” A natural consequence of hyper-specialization and more routinized tasks, freelancers will have little interest – or need – to grasp how the output of their work fits into the larger context.

5. Capacity sharing and more outsourcing. As freelance projects become more specialized, they will have shorter durations. Consequently, freelancers will increasingly distribute their time among larger portfolios of clients.

6. Lower transaction costs for acquiring talent. “Now that most people carry computers in their pockets which can keep them connected with each other, know where they are, understand their social network and so on, the transaction costs involved in finding people to do things can be pushed a long way down,” according to The Economist.

7. Lower billable rates for freelancers, too.Alfred, a subscription concierge service, is already aggregating the work of specific on-demand companies such as Instacart and Handy to offer its Boston members a one-stop shop; such aggregation could drive down prices for the basic on-demand providers yet further,” The Economist reported.

8. Increased reliance on trust. As corporate strategies increasingly depend on agility and shorter project lifecycles, they will seek greater certainties in the results that people produce. Conversely, freelancers don’t want hassles when collecting their fees. Expediency will require both parties to develop more reliable, less time-consuming ways to develop trust.

9. Smaller, more manageable infrastructure. Companies that engage freelance workers will depend on a well-oiled payables system versus a bevy of tech recruiters, middle managers, and human talent administrators.

10. Decreased loyalty from those performing the work. Your father’s gold pin, awarded after thirty years of service to his company, has become an anachronism. Now, it’s “I’m doing this task for whoever pays me the highest rate.”

11. Increased self-reliance among contractors and employees. In-house training and development? Kiss it goodbye. Freelancers won’t expect it, and they will pick up the tab as overhead for having greater control over their destinies. And employers will be more than happy to oblige.

12. Buyers will value consistency in experiences, not in fostering relationships. As more business functions are outsourced to freelancers, buyers will value having the same high-quality result, and they will care little about who is providing the service.

13. Companies that provide ancillary B2B services such as executive staffing, skills training, and compensation consulting, will experience less demand for their services.

Freelancing will continue to expand, and these developments will substantially change how businesses sell products and services. As you and your friend wrap up your sales launch meeting, you realize that in less than one hour, you just achieved what used to take companies months, even years, of aggravating trial and error. “Back in 2015, companies used to burn through so much cash doing this,” you exclaim as you close out your collaborative session. Your newly-assembled biz-dev team has hardly gotten to know one another. But that doesn’t matter – they’ve already started contacting prospects. No surprise that they’re not wasting one precious minute on anything not pre-qualified. The right results – it’s what they provide, and what you’re paying for.

Hiring freelancers will undoubtedly help companies acquire talent more quickly. But whether freelance workers will enable companies to execute strategies more effectively remains to be seen. Still, speedy and effective action provide powerful competitive advantages, The Economist tells us. “The knowledge economy is subject to the same forces as the industrial and service economies: routinisation, division of labour, and contracting out. A striking proportion of professional knowledge can be turned into routine action, and the division of labour can bring big efficiencies to the knowledge economy.”

Revenue Uncertainty – Part I: Known Unknowns, Unknown Unknowns, and Everything in between

“. . . There are known knowns; there are things we know we know. We also know there are known unknowns; that is to say, we know there are some things we do not know. But there are also unknown unknowns—the ones we don’t know we don’t know.”—Donald Rumsfeld

Rummy sure has a way with words, concealing some powerful insight within bureaucratic gobbledygook. For most of us, uncertainty appears to be one large, amorphous mass, and Rummy has tackled that problem with a distillation, albeit one that’s a tad verbose. We should applaud him for even taking this on.

Let’s put Rummy’s idea to work. Suppose your company has decided to sell an established product into a new market. You have knowledge about the past and assumptions about the future. You understand that there are many possible outcomes, some of which are likelier than others. You know that one outcome will prevail, and even though you are fixated on your goal, you don’t know exactly how things will turn out. Question: how do you ensure the outcome you get is the outcome you envisioned? (Hint: the answer is probably not stay the course. The people who coined the term agile will get upset.)

This describes a classic uncertainty problem, and one that is especially common in revenue creation. How do vendors sort through the universe of data, artifacts, anecdotes, and information to develop sufficient knowledge to place bets intelligently? Rummy’s taxonomy can help.

Three distinguishing characteristics of an intelligent bet are 1) the odds of winning are understood, 2) the bettor can sustain a failed outcome, and 3) the best possible result should be one worth having. As I’ve learned, smart people can make dumb bets, and the converse is also true – it doesn’t require extraordinary brainpower to make wagers that are remarkably astute. Something to consider before forking over a hefty chunk of venture capital to a high-IQ adult. Want an extreme frinstance? Click here to see eight defunct dot.com’s that purchased expensive ads during SuperBowl XXXIV. “Oops. The money was nice while it lasted.” Dealing successfully with uncertainty involves having at least a shred of common sense.

Imagine that Rummy has a seat at the table as part of your strategic team. Here’s how he might whiteboard your planned market entrance:

The Known-Known’s. Pretty straightforward, but known-known’s are a small fraction of needed information: names of target organizations and their executives. Regulatory restrictions and pending legislation. Major competitors. Revenue and other financial information for each prospect. Specific Key Performance Indicators. Industry trends.

The Known-Unknown’s. Typical stuff that marketers and salespeople ask about: Size of the market. Trends. Forces. Competitive strengths and weaknesses. Average length of the selling cycle. Pain points. Influencers, movers, and shakers. Level of buyer knowledge and understanding. Decision criteria. Buying processes. Internal politics. Competing projects. Motivation. Money and budgets. Biases. Perceived opportunities. Perceived risks. The list stretches from here to forever.

The Unknown-unknown’s. Everything else. Things that nobody ever thought to ask about or discover. Events that happened before, but went under the radar. Events that never happened before, but might happen. Customer backlash over who-knows-what that might have a measurable impact on revenue. Mistakes that will be made that no one even knew could be made. The metaphorical blindside tackle. What author Nassim Nicholas Taleb calls Black Swans.

Rummy’s taxonomy guides a useful, and much needed conversation about revenue uncertainty. In the last twenty years, we’ve made great strides in adding to the corpus of known-known’s, and we’ve come a long, long way in learning how to discover the known-unknown’s. But we’re still left dangling, because we know that categorization only takes us so far. We still must answer, “now what?” And for that, we need mathematical rigor. Eighty years before Rummy, economist Frank Knight, author of Risk, Uncertainty, and Profit, examined uncertainty under that lens, outlining three types: a priori probability, statistical probability, and estimates. I’ll stick to the high level, so hang in there with me.

a Priori probability. You have a box with 12 blocks, and you know up front that six are green and six are red. Assuming you cannot see into the box, what is the probability of drawing a red block? The probability distribution has been determined by definition. This is an iconic example in which an individual can place a bet based on straightforward calculation.

Statistical probability. Imagine the same box, but now you don’t know how many blocks are in it, or how many different colors there are. This uncertainty problem is more complicated, and therefore more difficult to cope with. The probability distribution of the result is can be described by statistical analysis of empirically-collected data. Therefore, the way to manage the uncertainty in this scenario is to keep drawing and keep recording the result until you have sufficient information about the outcomes on which to base a future projection.

Estimates. Again, imagine the same box, but this time, you have no knowledge whatsoever about its contents. It could be holding anything. Any data that you might choose to collect don’t lend themselves to any statistical analysis.

Knight was keenly aware of the dangers of conflating “the problem of intuitive estimation” with “the logic of probability,” whether a priori or statistical.

Here’s what he wrote: The liability of opinion or estimate to error must be radically distinguished from probability or chance of either type, for there is no possibility of forming in any way groups of instances of sufficient homogeneity to make possible a quantitative determination of true probability. Business decisions, for example, deal with situations which are far too unique, generally speaking, for any sort of statistical tabulation to have any value for guidance. The conception of an objectively measurable probability or chance is simply inapplicable . . .

Knight must be turning over in his grave today. I’d love to see his reaction watching sales executives discuss revenue forecasts, or listening to data wonks crow about the ‘predictive validity’ in their models for B2B decision-making. And I don’t see Knight endorsing any company’s policy for assigning increased purchase probability based on where a deal sits on a hypothetical sales process continuum. Yet, many companies abdicate probability to the “forecasting logic” embedded within their CRM applications, while their senior executives scratch their heads wondering why Sales can’t furnish a more accurate number. “If only our sales reps would populate the information we’re asking them for!” Hmmmm. Which unknown-unknown’s might you be referring to?

I’m not advocating that forecasts have no value, or that companies should discontinue preparing them. Only that we’re squandering opportunities to gain insight about what makes revenue uncertain, and we’re failing to use the insights that we do gain to reduce the volatility in revenue results.

We all want less uncertainty. I get that. But we expect people responsible for revenue generation to be prescient beyond their capacity – heck, beyond anyone’s capacity – and then kicking them in the rear when they are wrong. Happily, there’s a way out of this frustrating cycle. In Part II, Putting Uncertainty to Work at Your Company, I’ll cover how to create a repeatable process for identifying and assessing revenue uncertainties, and in Part III, How to Model Revenue Risk, I’ll show how probability distributions can be applied to specific uncertainties, and how to interpret and use the results.