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“No one ever achieved greatness by playing it safe.”

 

This quote is attributed to Harry J. Gray, an iconic business manager and philanthropist who, through acquisition, assembled one of America’s largest manufacturing corporations. During his career, he received numerous recognitions and honors and was inducted into the Junior Achievement National Business Hall of Fame. My guess is that Mr. Gray was an expert at risk assessment and containment.

 

Wikipedia defines risk as a consequence of action taken in spite of uncertainty. Given that uncertainty is a fact of life in business, risk management is not only unavoidable but essential. In the context of inventory management, the most common risk strategy against stock-outs is to purchase extra inventory as safety stock.


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A lot of focus has been placed on advanced and predictive analytics, and rightfully so. I have written many posts and have spoken publically on the merits of advanced analytics for several years now.

 

What I find disorienting and misleading are marketers harping on how important it is to adopt advanced analytics right now. The thing that they just don’t get (or maybe they don’t want to get?) is that an organization will need to transcend a series of analytical maturity levels before they can truly capitalize on the benefits of advanced and predictive analytics.


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Good relationships are good for business. Building a relationship with a vendor takes time. It’s not uncommon for a buyer to work with the same rep for many years. They become friends, share stories and have a routine. That’s all good, right? Turns out the answer may be “not so much”.

 

Would a vendor take advantage of a friendly relationship? Probably not, but when was the last time you actually reviewed a vendor’s performance? Is your vendor still bringing good value? Are you challenging the status quo?


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Previously in this series I wrote that the principles of agile software development are more important than the development process (see Agile Software Development: It’s not a process). Consequently there isn’t just one correct way to do software development – the approach must be based on a careful examination of the needs of each project.


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Source: MIT Sloan Management Review

In my last post, I introduced the longitudinal study that MIT Sloan Management Review has been conducting over the past five years. From 2010 to 2012 they indicated that 67% of those surveyed believed that analytics gave their organizations a competitive edge. In 2013, that figure stabilized at 66% revealing the so called ‘Moneyball Effect’ where leaders lost their competitive edge that they once enjoyed because followers matured and made analytics core competencies. In 2014, that trend continued, falling to 61%.

 

But why?


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When supply chain professionals plan for future demand, their thoughts gravitate to meeting customer service levels while minimizing the amount of capital tied up in inventory.  Demand planning is about having the right product in the right place at the right time … right? Four occurrences of the same word would cause my old English teacher to shudder at this excessive use of a word in a single sentence. However, let us return to the important business of meeting consumer demand without incurring the cost of excess inventory.


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If you don’t stand for something you’ll fall for anything!

 

That was one of my Dad’s favorite expressions and I think it’s wise; I try to live by it every day. It applies nicely to software development too where I put it in the following terms:

 

If you don’t have a vision for your product you’ll clutter it with lots of unnecessary features!

 

I’m sure that makes you think of some bad examples, eh? Me too!


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Once upon a time, agile software development was revolutionary and cellphones were for making cellphone calls, but those times are long gone. Agile is a mainstream best-practice and if you aren’t applying it then I must brand you a laggard. But agile has changed in the last decade, and not always for the better.

 

Back in 2001 it was generally recognized that the principles behind agile were its most important characteristic, but nowadays there is an unhelpful emphasis on its mechanics. The phrase “an agile process” is often heard even though one of those principles states that agile values “individuals and interactions over processes and tools”.

 

Or to put it another way:

 


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By now, most of you have probably heard of, or read, the book entitled Competing on Analytics by Thomas Davenport that demonstrates how some of the most successful organizations in the world have made analytics a core capability and integral to their strategic planning. MIT Sloan has been tracking this phenomenon since 2010 echoing Davenport’s findings. From 2010 to 2012 they indicated that 67% of those surveyed believed that analytics gave their organizations a competitive edge. However, in their last installment of their longitudinal study, something interesting happened. Something that I like to call the ‘Oakland Athletics Effect’.

 

Findings from the annual MIT analytics study


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Choosing the technology for a long-term project is a risky business – this season’s hottest software may be horribly out of fashion a year or two from now. That’s a big problem if you’ve built your supply chain on it; no-one wants to upgrade their software platform very often.

 

It’s a lot easier with the benefit of 20/20 hindsight. If you were building a new enterprise application today you’d choose a web architecture for maximum flexibility in deployment (i.e. servers either local or in the cloud, clients on any kind of device running a browser). On the server you’d probably choose to build on a software ecosystem like Java since it runs on any hardware and has wide industry support. But a lot of enterprise software vendors chose something else when they began their long-term development projects and are left regretting that now.


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