Love the 'taps' illustration.First, it happened to me in a B&B in Scotland, but the innkeeper played a purposeful role in the latency. She was tired of Yanks driving up her fuel bill so if you demanded really hot water the system had an internal 'rev limiter' that defaulted to somewhere between tepid and freezing. If you demanded only warm water from the tap, everything was peachy. Second, as a member of enterprise scale management teams I often thought our companies were like giant steamships that take miles and miles to turn. The problem was always that by the time you finished a turn, another one was always immediately required to respond to a changing market - the company leaves a series of 's' shapes in the wake behind. Eventually, everyone just gets seasick.
This may explain what generals call the trap of "fighting the last war." We're unable to see a situation for what it is, so we apply an old solution to a new problem.
What I experienced in the enterprise was a metric shit ton of investment in any and all data capture and analysis products that promised leading indicator predictions. (I imagine the same is going on today with ‘ai everything’). Companies like Oracle, Salesforce, and the Big 5 accounting/consultancy firms made serious bank, but from my perspective as the marketing leader these products’ output rarely added value. At one company during a CRM implementation we just started calling and interviewing every single salesperson (hundreds!) to figure out what the heck was really going on.
I like the idea of talking to the people on the front lines. The problem is that interviews and data capture can only show you the past, which doesn't always yield leading indicators. For that, you have to imagine, design, prototype, and test—in other words, push into the unknown.
Brilliant summary Marty. Love your insights and style of writing - it just keeps me reading. Thanks and keep them coming.
Love the 'taps' illustration.First, it happened to me in a B&B in Scotland, but the innkeeper played a purposeful role in the latency. She was tired of Yanks driving up her fuel bill so if you demanded really hot water the system had an internal 'rev limiter' that defaulted to somewhere between tepid and freezing. If you demanded only warm water from the tap, everything was peachy. Second, as a member of enterprise scale management teams I often thought our companies were like giant steamships that take miles and miles to turn. The problem was always that by the time you finished a turn, another one was always immediately required to respond to a changing market - the company leaves a series of 's' shapes in the wake behind. Eventually, everyone just gets seasick.
This may explain what generals call the trap of "fighting the last war." We're unable to see a situation for what it is, so we apply an old solution to a new problem.
What I experienced in the enterprise was a metric shit ton of investment in any and all data capture and analysis products that promised leading indicator predictions. (I imagine the same is going on today with ‘ai everything’). Companies like Oracle, Salesforce, and the Big 5 accounting/consultancy firms made serious bank, but from my perspective as the marketing leader these products’ output rarely added value. At one company during a CRM implementation we just started calling and interviewing every single salesperson (hundreds!) to figure out what the heck was really going on.
I like the idea of talking to the people on the front lines. The problem is that interviews and data capture can only show you the past, which doesn't always yield leading indicators. For that, you have to imagine, design, prototype, and test—in other words, push into the unknown.