Have We Moved Beyond Systems of Record?

Systems of record once held great promise for industrial businesses by storing a vast amount of data on how they operated. But have systems of record reached the point of diminishing returns? Heavy industries are turning to systems of intelligence to leverage that untapped knowledge base, uncovering ways of growing their revenue and lowering their operating costs.

In my recent talks with business leaders and the third-party analysts who advise them, a major theme has emerged: Today’s industrial companies are data-rich, yet insights-poor.

This has become increasingly problematic for heavy industry incumbents that, more and more, are being challenged by much younger, nimbler disruptors. Those disruptors don’t carry legacy technical debt, they’re faster to innovate and they’re quickly stealing market share.

Forward-thinking business leaders are trying to change that situation for the better. How so? By evolving their own mindsets about the role that technology can and should be playing in the process.

What are the best and brightest minds in the industry saying?

I recently attended this year’s Gartner Tech Growth and Innovation Conference, which examined where the rubber is hitting the road for emerging technologies.

The event was a gathering of the minds to discuss the latest developments in how companies are using new innovations to rethink and transform their businesses, and to remain competitive in dynamic markets.

Throughout the many sessions with top industry analysts, two key points crystallized, both of which have direct implications for industrial businesses:

1) We’ve entered the era of systems of intelligence, where a greater number of people are empowered to do their best work.

Systems of record once offered tremendous promise. They could store an incredible amount of data on how a business operates. That still holds true today — they contain a wealth of valuable information. However, systems of record have reached the point of diminishing returns. This perspective is rapidly gaining traction among business leaders and technologists alike.

So then, now what?

Industrial companies are turning to systems of intelligence to tap into that knowledge base — which, for decades, has largely gone overlooked and underutilized. They’re on a mission to use the data they’ve been sitting on for so long to uncover new ways of growing their revenue and lowering their operating costs. And it’s something that systems of record simply aren’t designed to do.

Systems of intelligence translate what’s happening in systems of record — like Enterprise Asset Management (EAM), Field Service Management (FSM), Enterprise Resource Planning (ERP), Customer Relationship Management (CRM) and Human Capital Management (HCM) — into meaningful insights that people can actually use to be even better at their jobs.

By nature, the systems themselves are capable of learning — growing smarter, faster and more accurate with each data point. Systems of intelligence operationalize insights so that those learnings can be consumed by the industrial workforce, by connected “things” and by entire other ecosystems.

Artificial intelligence (AI) is the driving force of the change described above. AI is ushering in a new era of software applications that turn vast amounts of data into actionable insights, predictions and recommendations for industrial workers of all roles. From the shop floor to the boardroom, more types of people can use that intelligence to make smarter decisions, see around corners and always stay one step ahead.

Here I want to make an important distinction:

It’s not enough just to feed new insights into legacy applications. It’s incumbent on technology providers to open up their systems so that they can bring in and share data from any source with any application. Openness is really the key. It’s how companies will unlock the true value of all the data they’re sitting on. In turn, AI will unlock even more opportunities for driving financial outcomes across the operating landscapes of industrial businesses.

2) In shifting markets, business leaders need to be taking steps right now to evolve, to avoid disruption and to not lose their market share.

Market disruption is inevitable. But it’s hard to predict which industries will be up-ended by the next Uber or Amazon sooner rather than later. Because it’s not a question of if, it’s a question of when. That’s why business leaders must stay on their toes. They need to be taking the right steps today to ensure their future is bright.

Traditional business models are shifting. As a result, industrial companies have to be able to adapt — quickly. It’s how they’ll stay relevant in changing times and not let their market share slip.

This can be readily observed in the world of Original Equipment Manufacturers (OEMs). The OEM market is shifting away from the traditional model of selling assets directly to customers, to a services-based model where customers pay a subscription fee based on usage or uptime of the OEM’s assets.

This is another area where AI can help.

As companies look to evolve their products and services in order to further differentiate their brands, AI can help them better understand how to do it successfully. AI is powering new industrial customer experiences by solving complex challenges across four key functional areas: channel growth, intelligent products, efficient operations and new business models.

What questions should you be asking your technology providers?

You’re not alone if you don’t know everything about AI. Frequently, I hear from industry analysts that it’s more important to know the right questions to ask of AI providers.

In that spirit, here are the top questions you should be asking them about AI:

  • How does your technology enable me to make better decisions faster? How do those decisions ultimately deliver value to my organization? What’s the business value and impact, and what does your AI solution do to help me achieve all of this?
  • How does your company support connecting to or integrating with systems of record and other data sources like historians and edge devices?
  • How does your AI solution empower me to make data-driven decisions about my customers? How does it help me bring them superior value and better customer experiences? How do you help me enable new and innovative business models?

Want to learn more? Check out our survival guide to AI and machine learning in the Fourth Industrial Revolution: