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Is Big Data the Silver Bullet for Supply Chain Analytics?

Leveraging “Big Data” is  coming up more and more as a “must have” in conversations I’m having with clients and prospects, not only in the food and beverage industry, but in other industries that have supply chain applications as an integral part of their operations.  The commonality between the companies I talk to is that they are all trying to seek out that additional growth, revenue and profit, and the lure of using Big Data to do so is very appealing.   Some of the pressure translates into more and more frequent requests by logistics and supply chain teams to use “Big Data” to optimize inventory allocation decisions and to develop a comprehensive view of what exactly is selling and at what velocity it is moving through the supply chain.  But is Big Data the super solution for besting competitors or driving value from in-house data that all hope it is?

The answer is it depends.

Intelligence Input = Sales Output

As true today as it was 50 years ago?

clock_raymajorTime capsules can be interesting. They can also be humbling. More on that in a moment.

When we hear time capsule, most of us think of a dented iron box filled with photos, knick-knacks and documents buried under the cornerstone of the courthouse in a Midwestern hamlet.  

Those doing the burying often specify the amount of time the capsule is to remain in the ground. In some cases, the timespan must remain undefined. For example, four well-known time capsules are "buried" in space. The two Pioneer Plaques and the two Voyager Golden Records were attached to spacecraft for the benefit of music-loving space-travelers in the distant future. Will they prefer Chuck Berry to Mozart? Inquiring minds want to know.

A fifth space-bound time capsule, the KEO satellite, to be launched circa 2016, will carry individual messages from Earth's inhabitants addressed to earthlings around the year 52,000, when it is due to return. Setting aside navigation and language issues, I suspect DVD player parts will be hard to come by then, even on Craigslist. Good luck with that.

Five Tips to consider when designing Supply Chain Key Performance Indicators

http://higherlogicdownload.s3.amazonaws.com/AXUG/UploadedImages/eb3c6bc2-b78d-4d20-9098-4a5c4f90dbeb/kpis.pngYou can’t predict anything with 100% certainty, and your predictive power wanes the farther out you gaze. The study of KPIs over time is all about finding patterns and signals, then applying intelligence in order to make better decisions and gain wisdom.

In a previous post I focused on the pitfalls associated with supply chain KPI and metrics development.  In this post, I’ll cover how businesses can improve their supply chain measurement processes by avoiding the common pitfalls by keeping in mind a few simple hints.

1) Don’t start by asking for a list of everyone’s metrics

You don’t need to create a collection of all things measurable. With massive amounts of new (and sometimes big) data being added to corporate databases every day, the permutations will grow and the questions that can be asked simply become more confusing. Start fresh and start at the top. Focus on KPIs that shed light on progress toward achieving strategic business goals.

Implementing Sales and Operations Planning, Why Oh Why is it so difficult?

Sometimes the hardest part about implementing Sales and Operations Planning (or any project) is just getting started

Sisyphus-e1298413740742A few weeks ago I was thinking about conversations I’ve been having with clients in the early stages of implementing an S&OP strategy.  They were relying on a phased approach, they knew that they needed an integrated set of business processes to go with their newly purchased technology.  They understood that the focus needed to be on information, not just the volumes of data they had at hand.  They knew that in order to implement a successful S&OP they needed clean, current, and accurate data.  As with many organizations, time and effort was being wasted gathering data that had minimal importance to the overall project.  But in this case, senior leadership was able to articulate the business problem they were trying to solve, and were able to help define, with some difficulty mind you, the minimum data necessary for the project.

It all sounds wonderful on paper, and we were destine for success!   But, like other businesses their attempts to implement S&OP were frustrated by internal tensions between departments.  What followed was this seemingly innocent statement on my part:  “Not everyone will be a convert immediately, so we watch for resistance and address it as part of our strategy.  Push, but not too hard, or we will get resistance.”

Is there one “Right” Strategy to Implement Business Intelligence?

Implementing a successful business intelligence strategy in the food and beverage industry is simple — just stick to a few key rules

statue_halobiblogThis past week, I spent a considerable amount of time with some of our food and beverage supply chain clients who are in the early stages of implementing a Business Intelligence Strategy. What I learned was interesting and reminded me of an old Hungarian saying my mom used to use – “Ahány ház, annyi szokás.” Knowing that many of you probably don’t read Hungarian, in English this translates to “There are as many customs as there are houses.”

So what does this have to do with BI strategies you ask? Well it seems from all my conversations that “there are as many BI implementation strategies as there are companies.” That got me thinking, is there one “right” strategy to implement BI? I don’t really think so. Just as each household is unique, and has its own set of customs, so is each business.

Each business, has its own set of needs and challenges. For instance, one client faces pressure from a growing number of store types catering to specific consumer needs, such as supercenters, membership clubs, and convenience stores.  Another is looking for opportunities to take advantage of the Consumer demand for more food options that meet a variety of needs, including health, taste and convenience, such as the “Gluten Free” fad. And yet another is trying to wrap its head around public policy and consumer sentiment is that is driving product traceability and fueling the demand for private label, organic foods and product freshness.

Because these challenges are so diverse, and for the most part these challenges are on top of all the other Business Intelligence work that a company has to do, each requires a unique BI implementation strategy. With that said, there are some commonalities that I think make life a little easier for everyone involved in rolling out a BI solution.

My advice: involve the end user; think big, but start small.

How do you turn Supply Chain Data in to Actionable Information?

Okay, so you’re committed to rolling out Business Intelligence across your supply chain, you have tons of data, so how do you turn that data in to actionable information?

TAGthink1There is a continuum in terms of presentation of data that allows for continuous sophistication in understanding and interpreting data.  There are lots of ways to view data, but three that are particularly useful in supply-chain analytics are --Reporting, Scorecarding, and Benchmarking.

The simplest form of looking at data is what we have all seen dozens of times, we call it “Reporting”.   Back in the day, reporting was numbers printed out on green bar paper, but today’s business intelligence reports are far more detailed and dynamic than in the past.  For instance, a BI report of today displays all the data about transportation providers as usable information, in a scorecard format. Factors such as on-time delivery, freight cost per unit shipped, and transit time are assigned metrics and weighted averages to help users determine how well carriers are performing overall.

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