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  • bobscheier

Mine the Past for IT Thought Leadership

Updated: Apr 9, 2022

We often think thought leadership requires uncovering some fundamental new truth about the universe, proving it is correct, and showing how to get there. That’s a heavy lift, and it’s not always possible – or even necessary.

Sometimes, just having been around the industry, seeing a thing or two, and applying that historic perspective to a new issue is enough. For evidence, see this recent blog post by aviation industry analyst Richard Aboulafia expressing his skepticism about the much-hyped emerging technology of very light aircraft and air taxis.

His piece looks not forward but back, to the early 2000s, and the death of an earlier generation of companies trying to make air travel easier and less expensive through, among other things, very small jets available for rent. He used his experience to list six reasons the current very light/very small “air mobility” market will collapse. They range from investors ignoring the high capital costs of the aircraft to a lack of serious engineering work to the human tendency to believe hype – all illustrated with detailed examples.

The lesson for IT marketers: Having been around and seeing several technology hype cycles gives your senior developers or executives the potential to develop compelling thought leadership. To do so, they need to look beyond the shiny surface of today’s tech toys for deeper trends and hard-learned lessons.

Several examples of how this could look like:

  • Data Lakehouses: The latest magic pill for our data woes? Look back on the history of traditional databases, data marts, data warehouses, and data lakes and why each failed to solve the perennial challenges of scale, cost, speed and data quality. What similar questions should we be asking about data lakehouses that we are not, and how should that affect product development, customer purchase choices and marketing?

  • Security: The problem that keeps sucking up more money but never seems to get better. We’ve moved from firewalls to securing APIs, from whitelist-based antivirus to AI-enabled behavior analysis, and from descriptive to predictive to prescriptive security and zero trust security. But there always seems to be new threats around the corner, and security managers struggle for budget in part because previous magic bullets failed. What questions should we be asking, but are not, about the latest and greatest security approaches? What new approaches should be consider, such as considering security spending like insurance premiums – a cost of doing business that mitigates, rather than eliminates, risk?

  • Cloud Everything: Once upon a time centralized IT was in, with most data processing going through a mainframe. Then decentralized-client server was the rage. Now, the big cloud hyperscalers provide central sources of compute, storage and networking and are the default choice for many workloads. Based on our lessons with previous computing models, what are the hidden weaknesses (from cost to security to vendor lockin to compliance) we’re missing in the move to cloud? When and why should companies consider keeping some internal IT capabilities?

  • Edge computing: This refers to the growth of processing and storage capabilities close to the edge of the network, quickly analyzing and acting on data from sensors, factory devices and vehicles. An industry veteran could look back at the spread of department-level local area networks in the 1980s for hard lessons about the need for standards, policies governing data sharing among groups, proper security and for making sure local “edge” infrastructure doesn’t become a hidden, unproductive drag on budgets. The technology may change, but the impulse to avoid slow, stodgy central IT to solve a pressing problem hasn’t. Nor have the problems of uncontrolled, local technology deployment.

Begin your quest for backward-looking thought leadership by asking your most experienced team members which recurrent problems or patterns they see, either in the underlying technology or business’ use of it. Then ask them to draw two or three hard-learned lessons from the past and apply them to the present.

They don’t have to be 100 % right in every one of your criticisms (or praise) of a technology or a business trend or their predictions. They just need a reasonable observation, connection, or question no one else has found. Getting the reader thinking alone new lines is real, and valuable, thought leadership in and of itself.

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