Our favorite craft brewer has a tap room. They never have more than a dozen beers on tap. They only serve their own brewed beers, never anything sourced from another producer. They have only marginal amounts of product distribution; for all intents and purposes, they sell only through their tap room. While they’ll fill a growler or crowler, they do not keep inventory in cans, only kegs. They turn over 2/3rds - maybe it’s 3/4ths, maybe it’s 7/8ths - of their taps seasonally, where a season might be as short as a month or as long as half a year, depending on the beer. They have a flat screen but never broadcast sports or politics, only streamed images of nature or trains or the like. They stream their own custom audio playlist to provide ambient noise.
They run the business this way because this is the business they want to run. They have direct access to 99.9% of their customers (not 100% as once it leaves the premises, the contents of a crowler could end up in anybody’s stomach…) They’re not committed to provide beer to other businesses on any kind of a product mix by volume, let alone date delivery schedule. They get to experiment with product, constantly. They don’t make what they sell, they sell what they make.
On any given day in the taproom, a customer will give them advice, a sentence that always begins with the words “you should.” Such as, “you should distribute this and that beer to these bars in Madison and Milwaukee - you’d sell 20x as much as you do in a single tap room.” Or, “you should have a small electric oven and sell food.” Or “you should have dozens of TVs with football and this place would be packed on weekends.”
They are every bit as good at customer interaction as they are with making and serving beer. They listen patiently, smile, and reply with “thank you, we’ll think about that.”
The software business has long been intertwined with management consulting to one degree or another. Decades ago, tech automated tasks that changed long standing business processes; management was fascinated as this made businesses more efficient. The dot-com era (followed by mobile, and shortly thereafter by social media) ushered in changes in corporate <— —> customer and —> employee interactions. The contemporary tech landscape (cloud, AI, distributed ledger tech) - and not for the first time in the history of tech - promises to “reinvent the business.” ‘Twas ever thus: tech has long been, and sought out as, a source of business advice.
On the whole, tech is not a source of bad advice. When tech gets close to a problem space, it brings a different and generally value generative solution. Why do that work manually when we can easily automate and orchestrate that? Why have this customer talk to that salesperson when the customer can do that for themselves 99% of the time? Why have people churn through that data when a machine can learn the patterns?
But sometimes, advice from tech is truly value destructive.
I wrote about this some years ago, but standing next to me in the queue for a flight out of Dallas were a couple of logistics consultants lamenting the fact that a client had taken a tech consultancy’s advice and prioritized flexibility over volume in their distribution strategy. It sounds great in a windowless conference room: why let restaurants (who are 80% of the clientele) run out of branzino before the night is over? You should run a fleet of small delivery trucks to top up their stock of branzino for the night in near real time. Except, the distribution cost for a few branzino to that restaurant - even if we put it in a small truck with a few packages of great northern beans to the restaurant down the street and some basmati to a restaurant a few blocks away - is bloody expensive. The economics of distribution are based on volume, not flexibility. That restaurant will have to put a lot of adjectives in front of the noun to justify the cost of limited-supplied branzino on a Tuesday in November. ’tis far more economically efficient for the waitstaff to push the red snapper when the branzino runs out.
Another time, I was working with a manufacturer of very large equipment. The manufacturer sold through a dealer network. Dealers are given guidance from the manufacturer’s sales forecasting division as to the volume of each type of machine they should expect to sell in the next two years, by quarter. Dealers order machines with that guidance as an input (their balance sheet being another input), and over the course of time dealer orders get routed to a manufacturing plant to the dealer sales lot. The tech people couldn’t grok this. Manufacturing something without a specific end customer? You should have just-in-time manufacturing, so a customer order goes directly to a manufacturing facility. That way there is no finished goods inventory collecting dust on a dealer lot and the component supply chain can be somehow further optimized. Except, that exposes the manufacturer to demand swings. As it is, the manufacturer has hundreds of dealer P&Ls to which it can export its own P&L. They’ll build give or take 250,000 units of this model, and give or take 160,000 units of that model, and give or take 90,000 units of that other model, and 000,000s of all those other models, year in and year out, with minor modifications in major product cycles in an industry regulated by, among other things, emission standards. That’s a lot of machine volume, especially when there are dozens and dozens of models of tens of thousands of unit volume. The manufacturer has a captive dealer network that will buy 100% of what the manufacturer produces. The dealer network acts as a buffer on the manufacturer’s P&L: while the good years may not be maximally great for the manufacturer, the bad years aren’t too terribly bad, let alone event horizons on the income statement. That, in turn, creates consistency of cash flows for the manufacturer, which investors reward with a high credit rating, which makes debt more easily serviceable, which leaves money to reward equity holders. Just-in-time manufacturing exposes the manufacturer to end-customer market volatility, which would require a substantial change in capital structure, which would penalize both equity and debt holders. Markets go up, but markets also go down: minimizing the downside was of more value than maximizing the upside. Tech has known these swings (anyone remember the home computer revolution?), but the commercial landscape is so destructive, there is a lack of instititional memory.
There was the insurance company implementing a workflow management system for automating policy renewal. Although insurance data is highly structured, there are a lot of rules and conditions on the rules governing renewal, spanning the micro (e.g., geographic location in a city and number of employees) and macro (discounting and payout rules in the event a customer has a property & casualty policy as well as an umbrella policy, as opposed to just a property & casualty policy). There are a lot of policy renewal rules that go very deep into the very edge cases of the edge cases (e.g., a policy that renews on February 29). Well, the boss wants this policy automation thing done quickly, because we have a great story to share with investors that we’ve reduced the labor intensity of policy renewal. Along comes a tech vendor with a compelling suggestion: insurance company, you should incentivize your process automation vendor by rewarding them for the shortest time to development of each codified rule. (The operative word here is development, which is not the same as production delivery: delivery was deemed out of the control of the development partner.) Except, the contract the insurance company signed indexed cash payable to the vendor for development complete of each rule. Within three months, the vendor had tapped out over 80% of the cash for software development, yet each rule that was dev complete had on average over five severity-1 defects associated with it and was therefore unsuitable for deployment. Worse still, one third of those defects were blocking, meaning there were countless other defects to discover once the blocking defect was removed.
Then there is the purely speculative pontification. I wrote three years ago that management consultants love to advise customers to get into the disruption game. Consider what was happening in home meals and transportation and the like 5 years ago: this is coming for your industry, so you better get in the game. To wit: hey financial services firm, you should invest in developing your own line of disruptive fintech. Except, in practice it turned out to be far more prudent for incumbents to colonize startup firms by placing people on startup firms boards and then co-opt them to the credit cycle through greenmail policies. The latter strategy was a hell of a lot cheaper than the former. And those home-meal- and food-delivery tech firms who were the reference implementation for disruption? They ended up disrupting one another, more than they disrupted the incumbents. Come to think of it, the winning strategy was that of the wise fighting fish in the movie From Russia, With Love: the stupid ones fight; the exhausted winner of that fight is easy prey for the smart fighting fish who sat out the fight and waited patiently. (Note to self: this is two consecutive months that I’ve used FRWL as an analogy, I really need to diversify my analogies. That said, Eric Pohlmann’s voiceover is truly underrated in cinematic history.)
This is, arguably, playing out today as auto manufacturers pull back from autonomous vehicle investments. Hey automotive firm, you should invest in autonomous vehicle delivery because it will totally disrupt the industry. Except, it’s proving to be much further away from reality than thought. It was great as long as delivery expectations were low and valuations were high. It isn’t so lucrative now.
Obviously, all advice has to meet a company where it’s at. Generic assertions of impending tech disruption in a well established industry crater instantly (even faster than crypto during a bank run) when they meet incumbent economic dynamics. People (especially long term employees) resist operational change; debt cycles outright crush those changes. Not meeting a company where it’s at renders the advisor a curious (and at best mildly amusing) pontificator.
At the same time, advice also has to meet the industry that consumer is in where it’s at. That’s not so easy when the advisor can only think transactionally. “Digital disruption” and “omnichannel” are, thankfully, out of favor now. They were ignorant of the industry dynamics at play, as mentioned earlier: co-opt the disruptor to the prevailing industry trends and the aspirant tech cycle is subservient to the credit cycle. It is (if ironically in evolutionary terms) well captured by Opus the penguin’s response to the allegedly inevitable.
One thing about being in the advisory space is that at a micro level, just about every firm has something - many somethings - unique to offer. (The caveat “just about” is intentional: it’s just about, but not all: as Mojo Nixon pointed out, Elvis is everywhere, but not in everyone.) “You should” advice that does not reflect that uniqueness - the expression of the company itself - is bound to fall flat. Yes, macro trends matter, but start with the business itself. If the people in that business know who they are and who they are not, you’ve got a great place to start. And if they don’t, the most Hyde Park Corner prophet of “disruption” isn’t going to hold an audience for long.
In the interest of full disclosure, we have, as you might well expect, been sources of what we deem brilliant “you should” advice to the aforementioned craft brewer. You should:
- Have a beer that incorporates cough syrup as an ingredient, a beer version of a Flaming Moe.
- Let me put my head underneath the taps like Barney Gumble when Moe isn’t around.
- Have drone delivery of your beer. Because drones.
- Have a trap door you can open that drops egregious “you should” pontificators into a pool of hungry alligators.
We’ve been assured that the proprietors are giving serious thought to every one of these.
