Clinical decision support Here, providers have two options, which can be used separately or together — evidence-based medicine and diagnosis support.
Technology Content Manufacturing companies are fast realizing that data and analytics can help tremendously in improving operational efficiencies and business processes, and in transforming business models — and they are investing heavily in it, says Jon Sobel, co-founder and CEO of Sight Machine, an analytics company focused on the manufacturing industry.
In a conversation with Knowledge Wharton, Sobel discusses the changing dynamics in the industry and explains why the focus of solution providers has shifted from offering local solutions to enterprise-level insights.
Following is an edited transcript of the conversation. Listen to the full podcast using the player above. Manufacturers are looking very systematically at everything they do, from the methods they use to make things, so technologies like 3-D printing and additive printing, all the way to their business models.
These large giant factories that have produced things are being broken up and distributed around the world to become much more flexible. First, [they want] to improve the efficiency of manufacturing operations — so time honored problems — how do we improve quality? How do we keep our factories running?
Next, [they want] to improving business processes and then all the way to business model transformation.
And they are starting to think very purposefully about using it. How big is the market? And what are some of the dynamics going on between manufacturing companies trying to become more digital and software companies entering the manufacturing space?
By most accounts, if we look at the Internet of Things market, McKinsey believes manufacturing is the largest opportunity of any industrial category.
Other firms echo that. The numbers that are thrown around as far as the expected value creation from using data and Internet of Things technologies are in the trillions over the next 10 years.
Many companies are trying to build do-it-yourself solutions, which is understandable. The major industrial companies such as GE and Siemens have invested, literally, billions of dollars in this opportunity.
One way to look at the market is to see all the people who are touching manufacturing. They all want to be a provider of analysis, of insight. Since you mentioned the collision, is there anyone who is winning this battle? Or is it still being played out? No clear winners yet. In our market, what we do — analyzing production data — the focus has shifted to scale.
If you think about the modern manufacturing enterprises, companies like GE have factories in their company alone, to say nothing of the thousands of factories in the supply chain.
So talking about your company — where do you see the opportunity to play in this space? Our company very early on focused on the scale analysis opportunity. The ingestion and analysis of huge amounts of varied data at once from multiple sources and multiple plants.
And what we did was to spend several years of building a sort of AI-enabled data engine for making sense of all of this data. And if what comes in from one side is a bunch of raw data, what should come out from the other side is useful information about production.
What happened was exactly what was supposed to happen for a startup.Sep 06, · I write books, deliver keynote presentations and provide expert advice on big data, analytics, metrics and improving business performance. I have helped many of the world’s leading companies and.
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