8 steps for a successful business case for your supply chain investments

Dr. MadhavDurbha

business case for your supply chain investmentsOver the years I’ve had the opportunity to engage in or witness the process organizations go through to prepare business cases in support of supply chain investments, from the successfully crafted and executed, to those that fail to gain traction.

Based on that experience, I wanted to share my eight most important pieces of advice for those being asked to prepare a business case for their supply chain investments.

  1. Ensure clarity on the strategic objectives of your organization.
    Any sizeable supply chain investment draws the attention of the senior leadership. Rightfully, your leadership will look to understand how the initiative supports the overall strategic objectives of the business. Being well versed with these objectives and able to demonstrate how the proposed initiative will support them is paramount to getting buy-in from your executives.
  2. Show how the initiative supports strategic objectives.
    Are your executives measured on servicing strategic customers better than your competition and reducing regulatory risks? If so, your business case will need to show how you can align with these objectives. For example, understanding your customers’ buying behaviors and segmenting and serving them based on these behaviors will help differentiate strategic customers. By enabling end-to-end visibility across your entire network, you can put a flashlight on looming regulatory risks. Make strong links between the strategic objectives and the enablers as directly and explicitly as possible.

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[On-Demand Webinar] Getting started with artificial intelligence in supply chain planning

AlexaCheater

Focus on a practical approach to implementing artificial intelligence (AI) and machine learning (ML) in your supply chain planning.

A pragmatic approach to getting started with artificial intelligence in supply chain planningThat’s the advice from industry-leading experts, as heard in our recent webinar, A pragmatic approach to getting started with artificial intelligence in supply chain planning, now available on-demand. Hosted by Robert Bowman from SupplyChainBrain, guest speakers Brian Tessier from Schneider Electric, Paul Cocuzzo from Merck and Trevor Miles from Kinaxis, discussed what you could do right now to take advantage of this trend.

From finding a practical application that provides tangible value for your business, to ensuring you have the right organizational structure in place, Tessier and Cocuzzo provided real-world advice driven by their organization’s own quests to implement AI in supply chain planning.

“Having AI take a world view based on best practices, and then applying it to your legacy data structures and business rules can give you insights into things you don’t even know are problems for you,” notes Tessier. “We found very quickly we had some very poor assumptions about lead times, both from suppliers and interplant shipments from within our supply chain. Given the number of transaction we do, the complexity of our product portfolio and the number of entities involved, there’s no way we would have found this any other way.”

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A Supply Chain Software Christmas Story

JonathanMatthews

Supply Chain Software Christmas Story T’was the night before Christmas and all through the house, not a creature was stirring, not even a… well, that’s not quite correct.

There was some stirring in the Clause house as Santa slowly shifted positions in his easy chair, looking out the window into the howling snow storm outside. The weather forecast said the storm would be blowing over soon and, and truth be told, it wasn’t that bad of a snowstorm. Certainly not like the famous storm eleven years ago.

But the weather had been poor the past month, and certainly not conducive for the last minute production crunch leading up to Christmas. Mentally preparing himself for the insanity the next 24 hours would bring, Santa mulled over the past year.

He should have been notified about production delays by now, but strangely, nothing had crossed his plate. Not even the unsavory incident he had overheard about in early November, when an elf drank a little too much eggnog and broke machinery, leading to a production delay. Even in the best years there are delays and problems. Right?

“Honey,” Santa Clause said softly, getting Mrs. Clause’s attention from the book she was reading. He noticed that it wasn’t her usual novel type book, but rather looked more like a technical manual. Without his glasses on, Santa didn’t try to strain his eyes to make out the title; he’d ask her later about it.

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Get your demand planning and forecasting game on

AlexaCheater

Outplay your competition with a smarter, stronger demand planning strategy

Demand Planning GameCustomer demands are changing. So why isn’t your demand planning strategy? It’s time to level up your demand planning and experience revolutionary breakthroughs in supply chain performance, planning and profitability.

Demand complexity is increasing thanks to consumers who now want more customization, omni-channel purchasing options, rush delivery, easy returns, and environmentally and ethically crafted merchandise, just to name a few present-day requirements. So how can your supply chain handle it all?

The key is to recognize solving today’s demand planning challenges just isn’t possible with yesterday’s dated processes and technology. It’s like trying to play Call of Duty: WWII on a system designed only to handle the technical requirements of Duck Hunt. The inevitable lag time, glitches and poor visibility destroys the experience. Yes, once upon a time you may have considered those old systems cutting edge. Now they just don’t have the capabilities you need.

Successful demand planning is quick, collaborative and up-to-date – not slow, siloed and full of stale data. It can’t take weeks to make critical decisions that don’t even align with reality. When changes to your demand plan happen, communication between business functions has to be immediate. Everyone needs to understand the ramifications of the change and come to a compromise-based corrective path.

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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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