The State of Analytics in the Industrial Environment
Drowning in Data and Starved for Information
Seeq® was founded on the premise that manufacturing organizations need better solutions for quickly and easily deriving business insight from their Industrial Process Data. Easier said than done: that founding, which occurred over 3 years ago, was followed by a first round of financing 2 years ago that enabled Seeq to ramp up in employees and customer engagements.
Now, as we prepare to introduce our first commercial release of Seeq, there are three things we’d like to share about Seeq and our perspective on the state of analytics in the industrial environment.
The first is to recognize the issues – and drudgery, and monotony, and repetitiveness – with achieving insights from production data. There are many ways to say this: DRIP (Data Rich, Information Poor), drowning in data and starved for information, the data deluge. Whatever you call it, we believe it’s too hard, and to continue Walt Mossberg’s theme from his first 1991 Wall Street Journal column, it’s not your fault. So Seeq is working to do something about it for you: make it easier, and faster, to get insights out of production data. “Easier”, “faster”, and “you” are the key words in that sentence. “Easier” and “faster” are clear enough, what about the “you”? You, the engineer or analyst with production and operations and asset knowledge, that is trying to get something done and has been left to muscle through the copying, cleansing, relating, and analyzing of production data. Yes, Seeq has an API, but you don’t have to use it to get insights, and you don’t need to go get an advanced degree in data science, either. For you, regardless of title or industry, struggling with insights from production data, Seeq is a productivity application designed to change the way you work. That’s why we are here.
Second is the phrase “Industrial Process Data,” why do we use that expression? The term is defined in several places on our web site, but why did we have to make it up in the first place? The reason is that insight frequently requires that data be placed or framed in a context that informs the data’s meaning. Zero miles an hour is good in a parking lot, but zero miles an hour is bad on a highway. That’s context. In the IT world, the relational data world, the terms for adding relevance to data include blending, harmonization, data fusion, augmentation, and enrichment. In the industrial world, or OT (Operational Technology) environment, most vendors favor “context” or “contextualization” as the term for framing data in the light of other data sets. As one vendor said at a recent conference “source data that’s been contextualized is information, then add knowledge and it becomes wisdom.” So if data needs context to be valuable, which system does that context come from? Which is why we use the “Industrial Process Data” term to reflect all the possible sources for data and context relevant to a particular plant. From EMI to EAM to CMMS to LIMS to ERP to BES to MES to the disks in your bottom left drawer, we need to be inclusive of all data sources that could make the difference in enabling insight. And rather than overwhelm every document with acronyms to cover all options and systems we simply say Industrial Process data to reflect all the potential data sources that could be required for insight.
Finally, how do we work? Seeq is a “modern” endeavor, a hard word for our CEO to hear since he took a class in “Modern Stochastic Models” in 1976. What does modern mean for Seeq? It means modern in development processes, in business model, in technology, and in organization. In development process, we use an agile approach with new functionality created in each 3-week sprint, and new features delivered to customers every quarter. Modern technology means tapping the open source and big data innovations that have revolutionized IT and consumer experiences over the last few years like Google, Tableau, and Atlassian. For business model “modern” means transparency in pricing and a user-based, subscription model. If you don’t use it, don’t pay for it! And with organization, we have employees across the United States, plus Canada and Europe. Where they are doesn’t matter, it’s working virtually with emphasis on customer experience that counts. As a result you can expect Seeq to be more like your consumer technology experience where you get to try before you buy, and time to new features is measured in months instead of years.
Welcome to Seeq and thank you for your interest!