Revisiting the Serendipity Economy: Tech Vendors Still Don’t Offer Value Propositions Beyond Productivity

Revisiting the Serendipity Economy

I recently discussed The Serendipity Economy with Don Findley on The Human Code (podcast available on October 8, here and on Apple and Spotify). I think it is time to rekindle a discussion about the real value of technology as AI sells its productivity message in many ways, to the detriment of other technologies, such as collaboration technology.

Cover image and animation by meta.ai.

Productivity, productivity, productivity

As an aside, collaboration technology boomed during the pandemic because lockdowns forced people to work remotely. It proved that people could work remotely effectively and garner other very positive side benefits, like feeling less stressed and spending more time with their families. It challenged the assumptions about colocation and the need for offices, at least large, communal offices.

Unfortunately, Microsoft, Cisco, Zoom, and others quickly leaned into the return-to-work movement led by organizations uncomfortable with people who don’t clock in or work where they can be seen. Poorly trained frontline managers didn’t know how to manage remote workers, and organizations didn’t know how to trust people who, for the most part, didn’t trust them.

I bring this up because The Serendipity Economy is largely a collaboration, a story, remote work, and a network of people and businesses that gain value through connection—value that can’t be determined at the time of purchase or even early in its use. The value of serendipity can’t be forecasted any more than the returns from a new sales presentation during its early outings.

Organizations can have hope, they can estimate, but until the document, which took less time to produce than last year’s version, is presented to customers, no one has any idea about what results it will yield. If those results are poor, then the productivity doesn’t matter. And in some cases, it may take weeks or months to realize the wasted effort.

Welcome to The Serendipity Economy

My idea for the Serendipity Economy arose from my long frustration with technology companies, including those that employed me, to explore the more profound value in their offerings. I thought they did a disservice to their products by only touting productivity gains. As a director or VP charged with thought leadership, I wanted to tell a more compelling story about value. I lived through the era of “computers turn up everywhere except in the numbers” as incremental claims at productivity failed to materialize in macroeconomic reports.

Technology vendors and buyers needed an alternative way to see the world. Organizations need more than a lens that sees how to do things more efficiently; they need a portal into how to create new value by leveraging the unique capabilities of a highly networked workforce and partner ecosystem. The productivity of the network wasn’t part of the story. Not only could we do tasks better, but the network reduced the points between people, increasing the likelihood that they might discover and deliver upon paths to value that could not be conceived by people isolated in cubicles doing their individual work ever more adroitly.

The message of productivity is too short-term. Hundreds of incremental reductions in effort across thousands of activities were easy to put into a spreadsheet. Simple experiments could be extrapolated into huge gains. The AI vendors are doing that now. They are taking small gains in an activity like reading an e-mail and adding up those seconds into minutes and hours, days and months until they produce a number bigger than the sales price of the technology.

Because of this extrapolation method, productivity appeals to buyers. They can justify a contract renewal based on the incremental technological improvements that will yield higher productivity and, therefore, produce off-setting cost reductions, usually in staff.

The people using the technology, on the other hand, often feel that they are productive enough. If they become more productive, they may find themselves or a colleague out of a job because the cost savings in productivity are jobs, regardless of what any messaging says from technology makers or employers.

A recent e-mail from Slack and Salesforce

Bullets from a recent Salesforce e-mail tell this story very effectively:

• 69% of sales professionals say their job is harder than ever.
• In this guide, discover how to speed up your sales process by:
  • Combining Salesforce Sales Cloud and Slack for 15% faster sales cycles
  • Using Slack Sales Elevate to bring real-time CRM data and insights right to the flow of work in Slack
  • Building better customer relationships with Slack Connect

The formula is clear. There is a pain point for sales professionals. 69% say their job is harder than ever. Then, there is the productivity promise of 15% faster sales cycles.

The accompanying download is titled “Transform your sales team’s productivity with Slack.” So, productivity. Not revenue growth. Not customer loyalty. Productivity of the team.

To some degree, the team’s productivity should be reflected in revenue and loyalty metrics. More time to engage, as the document promises, deeper relationships. The metric, however, on the “Forge deep relationships” page is 60% fast customer response times. That is a potential proof point for serendipity, as it speaks to technology facilitating touch points more quickly. The metric, however, stops at the touch without capturing the results. Do those faster touches (and BTW, it says faster, but it does not say more) result in more satisfaction and upsell, or are they just counted?

Before that metric, the paper looks to automation, a watchword for productivity selling. The page suggests “maximizing revenue per rep.” There are two ways to do that. Same revenue, fewer reps. More revenue, same or fewer reps. And then comes the 15% faster sales cycles from the e-mail. This is not a bad goal, but revenue per salesperson is a more effective way of measuring sales, including the touch and the close.

Any measurement that takes place after the production of something be it an e-mail, a phone call, a document, or a presentation, requires external validation to determine its value. Making something faster does not mean that it will land better. Making something faster in service to rapid learning cycles is also a great thing to measure, but it means accumulating productivity and serendipity.

Do the revisions take less time? Do the new messages land better than the old ones? And what do we mean by land? Do we get revenue? Do we see potential customers move from knowing nothing about an offer to being interested? Do they engage and reach out for more information, a demo? How does the technology of CRM, communications, and content creation accumulate throughout the value chain to deliver on any or all of those potential objectives?

My research shows that technology contributes beyond its surface value of helping people do things more quickly. It takes time to create models that capture that value, which must be in retrospect because all the value can’t be accounted for until the value is delivered.

Productivity (and competitive pressure) has been the stalwart for selling technology for decades. Neither the technology companies nor their customers really understand where technology plays a role. That lack of knowledge manifests in tools like Slack, which may co-exist with Microsoft Teams, chat inside of Webex or Zoom, or some other service like Discord, which also facilitates chats and channels. If just throwing technology at something increases productivity and profits, then more must be better. My experience tells me that isn’t true; frictions arise from duplication. Productivity decreases as people are forced to figure out where to work, where to store things, and which tool to use to communicate what.

If organizations understood the value chain of their information and knew more than how new tools made yesterday’s tasks faster, they would also know which tools and configurations got in the way of serendipity―what barriers exist to helping people work more smoothly with others, sell to them, or partner with them.

Serendipity happens if we account for it or not. Technology vendors must ask themselves how much money they may leave on the table because they can’t have a more sophisticated discussion about value, and their business customers may buy the wrong things or too many of the right things because the only measure of success they monitor is how fast things get done. A better model for how technology actually imparts value would help customers make better investment decisions and help technology companies better align their value propositions to real customer value.

Grammarly checked this blog post. It was wrong a few times. It helps me check my documents faster. My wife also proofreads everything after Grammarly is done with it. Neither of those creation efforts connected me with Don Findley and the team at The Human Code. I hope people will listen to the podcast, and I hope they visit SeriousInsights.net and read more about The Serendipity Economy and all of our other analyses and reviews.

Several months from now, someone may connect on a consulting engagement. Grammarly, my wife’s time, WPEngine, various WordPress plug-ins, my computer, and other investments led to that connection and that revenue. Technology may shrink the world and bring my words and voice to people I do not know, but they still need to be inspired, and they still need to act. And I don’t know when that will happen or at what level of revenue. Serendipity requires patience, which is the near opposite of productivity.

Productivity is just one element of value. Companies that buy technology might find more engaged vendors if they stopped buying their productive message and asked them to develop better models to prove the real value of their investments. That might also drive buyers to be more selective about the quantity of their technology choices.

With AI, organizations will face a new dilemma. Employees will ask multiple AIs for an answer and spend time determining which is best. That sounds productive.

Welcome to the Serendipity Economy

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