The PLM Insider
Jyotirmoy Dutta works as a PLM Lead Consultant at Infosys with more than 13 years of expertise in PLM Strategy Consulting, Solution Architecting, Offshore Project Management and Technical Leadership. He has led several full life-cycle PLM implementations, in the Consumer Products, Electronics & … More »
Competing on Analytics – Time for PLM based Analytics?
January 30th, 2012 by Jyotirmoy Dutta
This recent newspaper article caught my eye: “Mu Sigma receives $108 million funding” . “Mu Sigma, the analytics and decision-support services company, has received a $108 million investment round led by private equity firm General Atlantic. While $93 million came from General Atlantic, the remaining came from venture capital firm Sequoia Capital, which had previously (in April) led a $25-million round of funding of Mu Sigma.”
There has been some recent action going on in the analytics software market. In September, US-based predictive analytics provider Opera Solutions received $84 million in funding, which the Wall Street Journal said values the firm at $500 million. After acquiring crime data intelligence software developer i2, Big Blue bought Canadian risk management analytics software developer Algorithmics for $387 million in the same month.
Although BI tools have been there for more than a decade now, the recent fillip to analytics was in part provided by Thomas H. Davenport’s 2006 in his seminal article in Harvard Business Review “Competing on Analytics“. This was followed by two books, “Competing on Analytics: The New Science of Winning” in 2007 and “Analytics at Work: Smarter Decisions, Better Results” in 2010. To quote Davenport: “It’s virtually impossible to differentiate yourself from competitors based on products alone. Your rivals sell offerings similar to yours. And thanks to cheap offshore labor, you’re hard-pressed to beat overseas competitors on product cost. How to pull ahead of the pack? Become an analytics competitor: Use sophisticated data-collection technology and analysis to wring every last drop of value from all your business processes. With analytics, you discern not only what your customers want but also how much they’re willing to pay and what keeps them loyal.”
“In God we trust; all others must bring data.”
The catch phrase “Big Data” has been bubbling up from different vendors in the past few months. While it is debatable whether PLM systems would have “Big Data”, in a large organization which has such PLM system for a few years would have amassed a huge amount of data related to typically BOM’s, Product Structure Metadata, various types of associated documents, change management and transactional data related to business process activities. Typically all PLM vendors provide a search tool (though some provide an index-search tool too). However most of the vendors seem to be weak on providing an analytics tool. A PLM based analytics/BI product is should not be a just high end fancy reporting tool with low TCO, out-of-box templates etc. – there are some fundamental difference between reporting and analysis. While both draw upon the same collected data, reporting and analysis are very different in terms of their purpose, tasks, outputs, delivery, and value. Without a clear distinction of the differences, a PLM customer may sell itself short in one area (typically analysis) and not achieve the full benefits of its analytics investment. Analysis focuses on questioning, examining, interpreting, comparing, and confirming. [http://www.adobepress.com/articles/article.asp?p=1811387&seqNum=3]
“If you do not know how to ask the right question, you discover nothing.” – Deming
A PLM based analytics solution should clearly be able to do:
Five Emerging Trends in Analytics
In my opinion PLM vendors currently provide fragmented analytics tools – Most of them address only a very specific section of the addressable market need. Also the problem seems to be compounded by the fact that not only companies implement a closed-loop PLM system thereby making data collection much tougher. PLM vendors should start taking note of the emerging trends (specially the “big data” problem) and start providing value-added analytics products to customers.
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