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What Does Smart {Industry} Mean?

Ryan Frederick | May 13th, 2024 | Dublin,Ohio

The terms and similar ones don’t misrepresent the situation. They are indeed approaches that elevate a company’s capabilities and efficiencies, but words like smart and intelligent for a reason. Tech vendors, from tools to consultants, want a stark contrast between a customer’s current state and the state using their products and taking their advice. They want the future state to be represented by competent and intelligent. Hence, customers perceive the current state as being dumb.

No one wants to be perceived or labeled as dumb, so tech as a category creates new terms and categories that create an environment of aspiration for companies to go from being dumb to intelligent. Companies attempting to go from dumb to smart spend billions of dollars, with too much spending wasted on an amorphous goal of being smarter.

As I was writing this, I was curious about the number of types of intelligence. There isn’t an agreement on the number. I found references from 8 to 12. These are personal intelligence types, but they help to reinforce that when we are determining a person’s or company’s level of intelligence, there is a lot of interpretation.

Terms like Smart Manufacturing capture the essence of a technical evolution but often fail to deliver on the practicalities, dependencies, and risks of doing so. Too many attempts at becoming ‘smart’ leave companies in a worse position than before because they have more to manage and maintain without the payoff.

Becoming smarter is not a bad thing, but general intelligence for a company isn’t as important as specific intelligence. General intelligence is gaining knowledge to no particular end. Yes, things can be automated, connected, and integrated, but doing so as a broad objective isn’t as productive and valuable as to a specific end. Being generally smart makes a person great at Jeopardy, but the objective for companies is to execute better to deliver more value to customers and therefore generate more revenue and profit. Generic intelligence, while it may seem appealing, can lead to unforeseen challenges and inefficiencies that don’t serve companies nearly as well as it does individuals.

So what does this mean for companies? The question every company should ask about becoming more intelligent is to what specific end? To provide a better customer experience isn’t specific enough. To be more efficient isn’t either. Nor is it to empower team members with more data. Companies need to take the reins and get very specific on the outcomes of smart, intelligent, and other transformation efforts. By setting clear, specific goals, companies can avoid the pitfalls of generic intelligence and steer their transformation efforts toward success.

Because terms like Smart Manufacturing are broad, it is difficult for companies to execute against them. It can be executed only when something is narrowed and brought into clear terms and focus. The goal should not be to become a smart manufacturer or to be intelligently automated but to do so in an escalating manner that drives meaningful, specific outcomes. I used escalating in the previous sentence intentionally because one of the traps companies fall into is to attempt to boil the ocean out of the gate. Too many companies are starting on a journey of becoming digitally smarter, setting a course and expectation that is all or nothing. The all-or-nothing perspective sets them up for failure before they even start because it is unrealistic to expect to go from 0–100 without the knowledge and systems to do so. Smart, intelligent, and transformation initiatives must have a long-term vision and be supported by long-term architecture. Still, expectations should be more startup-like, with a 0–1 initial mentality. The initial objective shouldn’t be how we go from 0 to 100 but how we incrementally build to get there.

Hype can be overwhelming and intimidating. It can paint a picture for companies of being lesser than the industry and competitors in a way that causes an overreaction and unattainable expectations. Becoming a smart manufacturer, implementing intelligent automation, or transforming digitally are all worthwhile goals for mid-market organizations, but doing them on your terms and in a methodical manner is much less likely to produce the desired outcomes. Toning down the hype to what is pragmatic can be challenging but necessary.