Who doesn’t embrace the concept of management by exception? This is one of those universal concepts that suggest we should build processes that handle normal variations virtually automatically, and reserve our precious human capital to address the variances that have significant business impact. Like most great concepts, the real challenge lies in the application of […]
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It happens to be axiomatic that you cannot manage your inventory if you do not control your inventory.
Many times, I have been told, “Our people just don’t trust the numbers they see in the enterprise resource planning (ERP) system. Everything has to be double-checked.”
Usually, this statement is followed by some negative comment about the ERP system being unreliable.
After digging around a bit, more of the true picture emerges. The numbers (read: quantities) in the ERP system aren’t reliable because, while the company is busy “managing” its inventory, it has pretty much neglected the matter of “controlling” their inventory.
Faster, smarter, more profitable supply chain decisions
Transitioning from hype to reality, artificial intelligence (AI) is gaining momentum across industries thanks to an explosion in computing power and storage, the emergence of IoT (Internet of Things) and big data, and algorithmic advances. While there have been numerous examples of how AI can boost profits in supply chain execution—most notably in the form of autonomous vehicles and smart robotics—the benefits related to supply chain planning have largely been ignored.
But that’s starting to change as future-focused executives see the potential to improve profitability and productivity by making faster, smarter supply chain planning decisions. The first step in achieving those benefits is understanding AI and the other technologies associated with it, and where they can help improve your supply chain planning initiatives.
Rushing kids out the door, walking the dog, navigating traffic—life is complicated enough without having to deal with overly complex supply chain management processes. Unfortunately, increasing consumer demands, growing globalization and mounting pressure to stay profitable in an ever-changing world is the new reality, and for many it means working harder than ever.
Just because supply chains are getting more complex, doesn’t mean the job of managing them has to as well. Isn’t it time you simplified your day-to-day responsibilities, made room for a little more ‘me’ time and moved away from bracing for chaos every single day at work?
The first step in re-gaining your work-life balance and getting your sanity back is ditching the plethora of Excel files littering your desktop. To do it, you have to take a deep breath and say goodbye to running your supply chain from Excel. Instead, bring a little peace back into your life by harmonizing all that disparate data from multiple sources and legacy enterprise resource planning (ERP) systems and bringing it together in one solution.
Having access to all supply chain data in a single system means you’ll gain the ability to run what-if scenario simulations faster and more effectively. They’ll be no need to import and verify data from multiple sources, which will cut down on the potential for data errors or integrity issues, and speed up the decision-making process. No more fretting about whether your data’s up-to-date and accurate. Just think of all the time you’ll save not having to do multiple data pulls and merging Excel files. You might actually make it home on time for dinner!
I recently read this very interesting book, “Be the Business: CIOs in the new era of IT” by Martha Heller. In the book, the author made several very interesting observations about how the role of a Chief Information Officer is changing in the age of cloud computing, personalization of tech, and the rise of shadow IT. As I was reading the book, I couldn’t help but reflect on my own experience of working with IT organizations over the last two decades I have been in the supply chain business. Let us examine the shifts that happened. I will lean on the Supply Chain Planning space as an example and relate to the broader shifts in the role of IT in supply chain management.
1. The disillusionment with the establishment: In the late 90’s, i2 Technologies (the company where I started my career) was blazing a new trail in supply chain planning technology as most companies know it today. Manugistics was a strong contender to i2. However, the market was small enough that it was largely ignored by the big ERP vendors for a while. With the promise of these newer and exciting technologies at the time, IT organizations opted for a “best-of-breed” strategy bringing together the best of the ERP platforms and the specialty supply chain vendor capabilities.
Business processes are shifting. Technology is evolving. The Internet of Things (IoT) is exploding. Is your global end-to-end supply chain management (SCM) strategy set to keep up? Industry 4.0 is here, and it’s bringing with it a whole new world, one that’s likely going to involve substantial change to your IT infrastructure.
By 2020, Cisco predicts there will be 50 billion IoT connected devices. Gartner believes this will add $1.9 billion in economic value, resulting in IDC’s forecast of $7.1 trillion of IoT solutions sold within that same timeframe. Availability and utilization of data will be key in driving that growth.
Doing More with Available Data
The McKinsey Global Institute, a leading technology research firm, says less than one percent of available data is currently being accessed by businesses – who primarily mine it for alarms and real-time control. They say so much more can be done to use that data to help transform business processes and enable new business models through the use of optimization and prediction.
Industry 4.0 can’t just be driven by technological advances. There has to be strategy behind the selection, deployment and interaction of these new devices and networks. Zoltan Pekar, the VP of Roland DG’s Global SCM Division, recently discussed this very topic at Kinexions, the Kinaxis annual user and training conference. During his presentation, he noted two emerging technologies his company is focusing on as they move toward the future – artificial intelligence (AI) and machine-to-machine (M2M) interfaces.
This post concludes my inventory management blog series.
Throughout this series I’ve proposed an elevated role for the inventory manager that challenges the assumption that an inventory manager is a victim of his colleagues’ business decisions and plays only a limited role in formulating inventory results. Inventory management is not a stand-alone business process that occurs after other processes are complete. It is a high-level process that should be integrated into other supply chain planning processes including, at a minimum, sales and operations planning, master production scheduling and supply action management. Inventory managers should support multiple business objectives and should have business integrated targets related to inventory levels, customer service levels, total inventory cost, and inventory quality.
The inventory manager needs to act like an air traffic controller, effectively collaborating with his management peers to guide and coordinate their processes together in a way that leads to optimized inventory results. They should be able to update safety stock and order policy settings, and they should be able to collaborate on improvement initiatives related to lead-time optimization, supply and demand variability, and supply chain agility. It’s important for the inventory manager to have strong analytic skills and a deep understanding of the principles of supply chain management as a successful inventory manager will understand how to meet his targets without negative consequences in other areas of the business. The company should support the inventory manager with access to continuous learning resources and development courses to ensure they stay current and can take advantage of recent industry advancements.
Our partner Celestica recently published the following article, ‘Are you keeping your demand management process honest?’ The author, Eric C. Lange, Director of Demand Planning and S&OP Services at Celestica, examines forecast accuracy and the main components of a demand management measurement tool and process. We’ve outlined his recommendations below so you can help improve your forecast accuracy, leading to improved business operations and ultimately greater success.
Reporting Forecast Accuracy
Even with an established Sales and Operations Planning (S&OP) process, if you’re neglecting forecast accuracy measurement and reporting you’re missing a critical piece of the puzzle for demand management success. Yes, it’s often a difficult, time-consuming and complex endeavor, but not doing it limits the prospects for success for the entire process.
While calculating forecast accuracy is important, it’s not enough. You also need measurement and accuracy reports to determine the effectiveness of the entire demand management process.
There are three main components of a demand management measurement tool and process:
- Decide the method to calculate forecast accuracy
- Determine how to calculate and eliminate any forecast bias in the process
- Manage all necessary data to evaluate the effectiveness of the demand management process
Once these components are in place, it’s time to move on to determining added value in the forecast.