The supply chain planning system crystal ball

JohnWesterveld

supply chain planning crystal ballTwenty-five years ago, I bought my first personal computer. One of the first applications I installed was a cookbook — the killer home PC application of the time. The second application was Quicken to manage my finances. Funds were tight then and I really needed to keep tabs on my spending.

Every transaction was meticulously entered, every statement validated against my records. Then I discovered the calendar function. With the calendar, I was able to schedule my known income (paycheck) and my known expenses (car loan, mortgage, utilities, taxes, groceries, etc.) and Quicken would project my bank balance into the future.

For me, this was game changing!

When making discretionary purchases, I could look at my projection to make sure that if I made that purchase, I would have enough money in the bank, not only now, but at the end of the month when my mortgage and car loan came out. It was my crystal ball, and I regularly asked it questions like:

What if I buy that awesome new 27″ Sony Trinitron television this week, could I still make my mortgage payment? What if I save my money this month? Or don’t go out for supper on the weekend? Then could I buy it?

Today’s supply chain professionals need a crystal ball, too. The only difference is that the decisions are much more complex and far reaching than balancing my finances.

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Let’s be clear: Digitization is not the same as Digital Transformation

TrevorMiles

Much is being written about Artificial Intelligence (AI) and Machine Learning (ML) recently. It is the topic du jour. There is undoubtedly a lot of opportunity in this space for automating highly manual and repetitive tasks, and even for redefining tasks. But there is little evidence that we have even begun to explore the opportunity to redefine whole supply chain planning processes.

To be honest, I have some doubts about the use of AI or ML to assist significantly in this space. More importantly, there is compelling reason to rewrite many processes with or without AI/ML. Most supply chain planning process definitions date back to before the advent of computers. In fact, most organizational structures, which dictate the processes, date back to military concepts of communications.

Process definition

 

 

 

 

 

 

I was prompted to write this blog based on an article published in Inc on Aug 30, 2017: This Email From Elon Musk to Tesla Employees Describes What Great Communication Looks Like. I will quote from the article quite liberally because there is a lot that Musk writes that is relevant to this discussion.

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Data integrity: Bad data and 3 good things to do about it when supply chain planning

BillDuBois

Supply chain planning - data integrityEvery business plans, but not every business runs as planned. Delays, shortages, quality issues, catastrophic weather events and fluctuating commodity prices are just a few examples of the exhaustive list of worries that will throw plan into disarray. Achieving a realistic forecast and aligning supply plans is an extreme long shot at best. The best supply chains need to manage business when it’s not business as usual. That’s what sets them apart.

However, even the best supply chains struggle with a recurring issue – data integrity. The alignment of demand and supply is more difficult because most, if not all, supply chains have data integrity issues. That means even if you take away all the supply chain disruptions, your plans are off before you even get started.

Successful supply chain planning starts with data

Setting yourself up for successful planning starts with your data. What could arguably be the single biggest deterrent to undertaking a supply chain planning improvement project is, “my data is crap.” Even though it’s likely true, you’re using the current state of your data to plan, and there’s still value in that. Data integrity shouldn’t be the reason not to take on a process improvement initiative, it should be a part of any supply chain planning improvement project.

Why the data issues?

Like the supply chain disruptions listed earlier, there are just as many reasons why data accuracy is as difficult as maintaining forecast accuracy. Here are the big reasons:

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TrinityRail ditches operational forecasting, gains sense and respond supply chain

AlexaCheater

TrinityRail Supply chain managementSupply chain management without an operational forecast – is it possible?

Yes. Yes it is. At least if you’re one of the world’s largest providers of railcar services and products. TrinityRail, part of Trinity Industries, Inc., ditched operational forecasting in favor of a sense and respond supply chain, and the results speak for themselves.

As outlined in a recent Kinaxis case study, TrinityRail was able to realize sizable improvements in its supply chain, including nearly removing its reliance on Excel for planning and dramatically reducing the need for manual data transfers. Using supply chain management software that connected its data, processes and people into a single, harmonized system, TrinityRail reduced the risk of error, since everyone was using the same, up-to-date data set. It was even able to reduce its days of inventory on-hand (DIOH) by an average of 12 days and reduce its buyer team by more than 25% while still improving the on-time delivery (OTD) of inbound materials.

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Supply chain visibility: The key to growth

JohnWesterveld

Supply chain visibility growthI came across a KPMG study last week covering a survey of 360 senior executives Forbes Insights did in 2016. There were a couple of key takeaways from the report:

  1. Manufacturers are planning on growth, but the overall market isn’t likely to grow. This means companies will need to battle for a bigger piece of the pie.
  2. The need for supply chain visibility is greater than ever, yet only half of the executives surveyed say they have the visibility they need to make decisions and mitigate risk.

Let’s dig into both of these highlights a bit more.

Growth within a static market

According to the study, most companies are planning to grow by entering new sectors, new geographic areas or by adding to the products and services on offer. The challenge is that other companies are looking to grow (73 percent of companies say growth in the next two years is a high to extremely high priority).

“Every company wants profitable growth. But according to our data, today’s manufacturers are much more focused on driving new growth than ever before.”

At the same time, baseline growth is expected to be limited. This means that for your company to be successful, you’ll need to outperform the other companies vying for the same market share. Your supply chain plays a key role: getting your product to market with excellent quality, in the quantity needed, at the right price, with the right design.

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Forecasting and demand management for new events using machine-learning algorithm

ImanNiroomand

Football - demand planning and forecastingWhat does a machine-learning (ML) algorithm have to do with the Super Bowl?

When it comes to forecasting and demand management, a lot.

Consider this: According to the National Retail Federation, approximately 189 million people watched Super Bowl LI, and viewers spent an average of $82.19 on electronics, apparel and food specifically for the game, up from $77.88 compared to the previous year.

For events like the Super Bowl, retail demand planners create forecasts using data from a variety of sources to adjust product demand profiles in anticipation of which product, or group of products might be in demand the most.

This is a daunting task when one considers the variety of products available to football fans – from cheeseheads to cheezies and everything in between. In the past, only about one brand in 50 was able to precisely adjust their football-frenzy driven supply chain to meet demand during the short two-week window between the conference championship games and the Super Bowl.

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Stranger supply chain things: Capacity planning lessons from Stranger Things

MikeMcAllister
Stranger Things
Courtesy of the Science Museum of Minnesota/Netflix

As a teenager in the 80s, it probably comes as no surprise I relate heavily to every cultural reference in Stranger Things. From the hair (I coveted to Steve’s A-Ha inspired coif) to the arcade (DigDug not so much – I would spend my allowance quarter by quarter on Star Castle and Defender, instead) and everything in between, the binge-watch worthy Netflix series contains pop culture Easter eggs in virtually every scene.

Which brings us to Dustin’s purple brontosaurus hoodie from Episode 1 of Stranger Things 2 – apparently purchased at The Science Museum of Minnesota, perhaps while on a road trip with his mom during the summer between season one and season two. This seemingly innocuous vintage piece of costuming features the logo of a popular touring fossil exhibit popular in the 80s known as “Thunder Lizard”.

Picking up on the appearance of their brand on the show, the museum scrambled to add the hoodie to their online and brick and mortar store. Smart move. Why not capitalize on the most anticipated release of the fall entertainment season?

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An optimist’s view of Blockchain in supply chain: Learnings from Bitcoin

Dr. MadhavDurbha

BitcoinThese days, not a single supply chain conference I attend goes by without someone mentioning Blockchain. Given the growing chatter, I wanted to share my views on the topic. In fact, my interest in Blockchain further increased as I started dabbling in Bitcoin, an application of the Blockchain technology.

As per Wikipedia, a Blockchain is a continuously growing list of records, called blocks, which are linked and secured using cryptography. Bitcoin is a form of decentralized digital cryptocurrency, not controlled by any nation or issuing bank.

Launched in 2009, Bitcoin was initially written off as a scam or fad. However, to the surprise of naysayers, Bitcoin did survive and is thriving, building quite a following. Here are some factors that are making Bitcoin a very attractive proposition, which are a direct result of the underlying Blockchain technology:

  1. Secure encrypted transactions ensuring privacy of the involved parties: Through a combination of public and private key encryptions facilitated by Blockchain, Bitcoin provides a virtually hacker-proof way of making and receiving payments. This is quite fascinating considering the code behind Bitcoin itself is open source. In a Blockchain, each transaction is recorded to a “block” across a large number of distributed systems. This transaction is then authenticated by each node in the network and is facilitated by individuals like you and me, who are referred to as “miners” in the Bitcoin world. Once recorded, the transaction cannot be altered, and it forever resides in a public distributed ledger that’s shared between the network nodes. The identity of the sender and receiver are protected through the encryption mechanisms. Not surprisingly, some of the early adopters of Bitcoin were those dealing in illegal goods and drugs through the now defunct Silkroad, online marketplace being the most prominent. While any technology can be put to both good and bad use, supply chains require a high degree of privacy and security to ensure validity of transactions for perfectly legitimate reasons – which Blockchain can enable.

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