The New Intelligent Enterprise

In last week’s blog, I outlined what I thought future companies would look like vis-à-vis their information technology and decision-making capabilities. I believe they’ll be intelligent, connected, and agile. Over the next several weeks, I’m going to dive deeper into how I think companies will realize their futures. And, as I’ve said, that future is not truly five years from now. It is now.

This week I’m going to explore how smart companies will leverage new technologies to become more intelligent. I’ll use the manufacturing sector as a prism for looking at how intelligence will differentiate companies from their competitors and enable them to thrive in a global, competitive network that leaves little margin for error.

On a good day in a production facility, things go smoothly. Everything functions as it should: parts roll in, products roll out, and production managers can breathe a sigh of relief at the end of the day. Good days don’t breed successful companies; they breed complacent ones. True success is bred by how well you deal with the bad days — and solve the problems that created them.

It happens to every company. Machines go down, diagnosis and repairs take critical, revenue-eating time. If the parts are local, the repair is quicker, but if they’re sourced nationally or globally, the company could be looking at loss runs in the millions of dollars. That’s for one production facility.

Intelligence and insight become scarce commodities.

Most large companies don’t just have one plant; they have several — and those are typically located globally, exacerbating problems. Connectivity between plants is often spotty, and each plant typically comes up with its own solution to problems. Data is collected and created, but so are silos. Intelligence and insight become scarce commodities.

Going forward, successful companies will reimagine their future and deploy analytics augmented with artificial intelligence (AI) across their entire value chain. Why AI? Because machines can be trained to learn, to recognize patterns and trends, to spot changes and exceptions, and suggest alternatives that may not be apparent to humans. Humans can then be presented with deep, relevant data they need to inform their decision-making process.

But there’s another benefit. When companies use AI to create intelligent analytics and gain better decision-making at one node in the value chain, those results can be applied across the entire production and logistics network to make the company smarter and more responsive. More than that, companies can predict problems — and head them off — before they happen.

As an example, let’s look at a global energy producer. The company might have thousands of wells and production facilities in 20 countries. What happens when a well breaks down, when three, or five, or ten wells break down simultaneously? Millions in revenue per day could potentially be lost.

However, using AI, the company can install sensors on their equipment to analyze performance across their production network and predict maintenance failures and repair needs. Downtime can be planned. Decision-makers can schedule production re-routes and revenue losses can be reduced or eliminated.

This example is only one instance where intelligent analytics can be used to control production networks and make smarter, faster decisions. Other uses include:

• Critical component tracking
• Delivery variability analysis
• Predictive maintenance
• Product and process efficiency and quality analysis
• Safety improvement
• Supplier quality analysis

Intelligent analytics will revolutionize how companies handle their data and operations. However, there’s a caveat. Intelligent analytics capabilities must be deployed in weeks, not months. The analytics companies deploy must combine the rich insights of analytics with the promise of data science to generate proof-of-concept models that can show improvements quickly and be propagated throughout the enterprise and generate quick, measurable ROI.

Intelligent analytics capabilities must be deployed in weeks, not months.

The bottom line here is about the impact to your business outcomes. Intelligent analytics can help you become smarter, faster, and more responsive. It can help you understand not only what’s happening, but why it’s happening — and most critically — what might happen in the future so that you can begin to control that future and make it work for you, not against you, so that you can differentiate yourself from your competitors and own the market.