After a decade at Salesforce as the VP of Strategic Research, and two decades before that as a columnist and editor in technology media, Peter Coffee is in a great position to share his advice on what makes for successful organizations – and what doesn’t.
Join us at #TF17 to hear about how the tech landscape has changed and what organizations need to do to become adaptive enterprises.
Q. This year’s focus is the adaptive enterprise. In what way does this term resonate with you?
A. My favourite Tom Peters book is Thriving on Chaos, in which he actually apologizes for the naïveté of the much-better-known In Search of Excellence. Tom found, on return examination, that many of his so-called “excellent companies” had fared poorly if they stuck to the behaviours that he had previously identified as their strengths; that it was companies showing the most adaptability and readiness for change who had done best. Since then, he has offered many variations on the idea that “adaptability is the only sustainable excellence,” and I have vigorously shared that opinion with many Salesforce customers, as well as with my teammates.
Q. When it comes to collecting and analyzing data, what do you think is the usual shortfall on the company’s end?
A. The greatest hazard in becoming data-driven is the temptation to collect the data that is most timely, most precise, and available in greatest quality at lowest cost. Those might sound like good attributes, but their pursuit is a recipe for the “streetlight effect” – the tendency to look where the looking is easy, rather than where the target of the search is perhaps more likely to be. I discuss these and other hazards of data collection in a blog post Stop looking under the lamp post on diginomica.
Q. How should companies use data?
A. The purpose of data yesterday was to document what had been done; the goal was efficiency. The purpose of data tomorrow is to seek out surprise, often wrapped in pain. The goal is deciding what to do next and that may entail unwelcome behaviour change. People have positive feelings about knowing what they did yesterday and using that as a basis for planning their tomorrow, but externally originating data will come at inconvenient times and in often-ambiguous combinations. Data science is simply the application of scientific method to data flows and collections, with all the difficulty that implies in forming and testing hypotheses with constructive skepticism.
Q. TractionForce is a business transformation event. What is your advice to companies wanting to make a big transformation?
A. I offer a four-part framework for companies who want to get serious about transformation. Are you prepared to do the hard work of becoming connected to the world? Are you prepared to reward those who connect with you by demonstrating awareness of what they share? Are you using the technologies of machine learning and other AI disciplines to become smart and therefore scalable? Are you doing all of this with an emphasis on earning and preserving trust? The acronym CAST – Connected, Aware, Smart, Trusted – captures the simplicity but also makes clear the full-team responsibility for making this a reality.
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