Is Vendor Selection Really The First Step in ERP Implementation?

A free guide that you can download from ERP Focus makes vendor selection the first of an 11-step implementation process, while defining success is the last.  In other words, they have you choose who you buy from before having a clear idea of what you are trying to accomplish.

It reminds me of a meeting at a client site where ERP implementation was about to begin. “This train has left the station,” I was told. The purpose of the meeting was to draw a “Value Stream Map” for the whole plant, in preparation for ERP, and the participants included managers from Manufacturing, Quality, Production Control, Maintenance, Purchasing, Sales, and Engineering.

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Turning Success into Mediocrity | Bill Waddell

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“… the lack of interest [in Lean] comes through loud and clear when you read the none-too-subtle message in this interview with Melissa Cook from Microsoft, ironically titled with a quote from her, Microsoft Director: ‘Manufacturing Is A Hotbed Of Innovation’.  She is all  about creativity, speed and innovation so long as it happens within the ERP framework.  Her examples of manufacturing’s creative culture is simply the evolution of MRP:  ‘going through MRP, MRPII and ERP. Manufacturing is a hotbed of innovation’…”

Michel Baudin‘s insight:

For decades, Microsoft has made money from selling buggy and functionally mediocre software to customers who couldn’t tell they had alternatives. And once Microsoft dominated a market, their products were a standard and mandatory if you wanted to exchange data with anyone you did business with.

With this background, I don’t find it surprising that the Microsoft people should consider ERP a success story. In manufacturing, a first generation of ignorant managers was sold the MRP bill of goods. It didn’t produce the expected benefits, but then, a new generation came on board that was the perfect mark for Closed-loop MRP, and the pattern repeated itself on a larger scale with each generation all the way to ERP.

It is a marvel of marketing that the failure of each generation of this type of software has not hurt the marketability of the next. And I think the key reason is that new managers are born, if not every minute, at least at the end of every academic year.

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Big Data – The Antithesis of Lean Thinking | Bill Waddell

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“It’s too bad lean thinking is free.  I suppose that’s not entirely true; a lean transformation actually costs a few bucks for the learning – consultants, books and training.  But it is nothing like the cost of an ERP system, and it pales in comparison to ERP thinking on steroids – ‘Big Data’.  Because the ERP and Big Data providers play in such a high dollar arena they can and do spend a lot on very focused marketing efforts.  IBM, a company that stands to gain quite a bit from Big Data becoming the focus of business management, is providing “software, curriculum, case studies—including guest speakers” to Rensselaer Polytechnic Institute, Fordham, Yale and about 300 other schools.  Too bad those schools aren’t cranking out kids steeped in lean thinking, but there is no one who stands to make a enough money from peddling lean in a position to buy college curriculums on such a scale…”

Michel Baudin‘s insight:

While I concur with Bill on the irrelevance of “Big Data” in manufacturing, I can’t follow him when he says it is a “singularly bad idea” for business in general.

Big Data, per se, is actually not an idea but a phenomenon experienced in companies like Google, Amazon, eBay, Netflix, and others that process clicks, queries and transactions from millions of users, and generatie Terabytes of data every day. This is what Big Data is. Making sense of it is vital to these companies, and its volume requires special technology.

Even in a large manufacturing company, specs, orders, production status and history, quality problem reports, etc., add up to Gibabytes of data in total, not Terabytes every day. While it is beyond what you can handle on an Excel spreadsheet, it does not qualify as Big Data and does not require the special technology that ecommerce companies have developed.

I also agree that the hot dog example from the HBR blog is simplistic. To give a less trivial example, assume you are in the business of providing streaming videos, and you discover from your customer data that those who view “Tora, Tora, Tora” also tend to view “The Bridges of Madison County.” That is unexpected and you wonder why. Then you find out that the customers who view both are married couples, form which you infer that the wife demands a chick flick for every aircraft-carrier movie…

This is a made-up example, but Ed Frazelle, in Supply Chain Strategy, quotes a real one about on-line ordering patterns for clothing. What kind of garments do customers tend to order together? I have asked that question around, and never met anyone who came up with the right answer, although, once you know it, it makes perfect sense: they order the same garment, in the same size, in different colors. And it is good to know if you are in charge of order picking.

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