When you consider the Automotive industry, business in the sector stock everything from pressure washers to chamois cloths, seasonality can have a massive influence on demand.
Given the potential for considerable fluctuations in demand, this can leave businesses exposed to a high level of uncertainty. For instance, when exactly does a new season start? When does the season finish? How can you be sure to what impact the seasonal influence will have on-demand? Unless a business takes steps to control all of these factors, seasonal spikes in demand can quickly spiral out of control.
For some seasonal products, the uplift in demand can be easily anticipated. This is not rocket science: you know that these articles have a seasonal demand pattern. However, what you don’t know is precisely when the season will start as this is dependent on a whole range of factors such as the consumer’s mindset or even the weather.
To help you optimize your operations before, during and after a seasonal peak, we have highlighted 8 top tips covering the following points to help you stay ahead of demand fluctuations:
- Achieve optimal stock levels before, after and during a seasonal peak
- Align service levels with customer expectations
- Guarantee availability of seasonal products while avoiding excess stock
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Having thousands and thousands of products and trying to maintain 100% availability throughout the assortment would make most of the suppliers bankrupt. At the same time, customers cannot afford to put their project on hold because certain items, materials or components are sold out. So what can the supply chain do to improve availability without exploiting costs?
FIND THE BALANCE BETWEEN THE RELIABILITY AND COSTS OF THE SUPPLY CHAIN
Ultimately, service levels are a direct translation of corporate strategy and inventory strategy. As such, companies determine the extent to which they can meet the needs of their customers based on stock capacity. For many organizations, this is about finding a balance between the strategic desire to improve stock availability and the need to meet current financial constraints.
IMPROVE STOCK AVAILABILITY WHERE MORE AMOUNT
For many companies, the criteria for establishing these service levels are not clear. As a result, many organizations rely on the inadequate levels of service that, at best, are determined based on a quick and vague analysis. For example, when the level of service hurts the safety stock or the stocks, we have to review and adjust quickly (again, without any real analysis).
Finding an optimal level of service allows companies to focus their investments and efforts, which in turn helps increase availability in the items that are most needed. However, for a service level strategy to be truly effective, it must take into account a large number of components, including billing, capacity, customer demand and cost.
Find out how you can offer your customers a more reliable service with our 5-step guide. Through these steps, you can increase levels of availability and customer satisfaction while reducing supply chain costs.
Download our guide and start optimizing your service levels today !!
Launching a new product comes with great risk. Even if the product launch is a success, if the company fails to determine the customer demand for the product then you could face a massive disaster. So what can you do to rationalize the decision-making process in order to commit to a new product introduction with confidence?
Slimstock Canada, along with Supply Chain Management Ontario conducted a speaking session on the topic "Managing the Unknown- New Product Introduction," on June 20th, 2019 in Hazelton Manor, Concord, ON. The event was filled to the brim with supply chain professionals from HD Supply, Amazon, Freedom Mobile, Apotex and many more. Danny Bloem, our very own supply chain expert, shared insights on the strategies of inventory management during new product introduction and how to determine the demand and supply during a challenging time.
HOW CAN YOU ESTIMATE DEMAND IN ADVANCE OF A NEW PRODUCT INTRODUCTION?
Launching a new product is an exciting time for any business. However, working out how exactly how much demand to expect can be a real challenge. On one hand, if the new product introduction is a roaring success, you want to ensure you have enough stock to exploit the sales opportunity fully. Equally, if you overestimate demand, this could easily result in a huge amount of excess. Consequently, it’s vital that when anticipating demand, you remain realistic!
IS THERE SUFFICIENT MARGIN TO JUSTIFY A NEW PRODUCT INTRODUCTION?
Even if there is plenty of interest in your new product concept, there is little point in pursuing a new product introduction if it will never achieve a sufficient return on investment. As a result, it is important that you do your homework before making any final decisions. Through confirming costs, order volumes and lead times with suppliers, it will quickly become evident whether it’s worth taking the risk.
If your product offers an ample return than that is a positive indication to proceed with a new product introduction. However, if the margins are not quite enough, perhaps the supplier is willing to negotiate on prices. Alternatively, maybe you can work with your customers to increase the sales volume.
TO LAUNCH, OR NOT TO LAUNCH
Download our latest infographic and discover what considerations you need to make in order to justify a new product introduction.
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Supplier closures are disruptive at the best of times. However, as your suppliers down tools to enjoy a well-deserved summer break, your business could become dangerously exposed to lengthy lead times, delays and even stock outs. What can you do to maintain a harmonious operation during what could be an extremely volatile time for your organization?
Contrary to popular belief, Mediterranean countries are not the only ones where it is common for factories to close down at some point during the summer: for Suppliers based in North America, Germany, France and even the UK, there is a good chance their operations could be brought to a standstill for a least a couple of weeks. Furthermore, unlike other factory closures periods, the summer season can last for several months and suppliers can shut down at any point throughout this time. Consequently, the potential impact of summer supplier closures cannot be understated!
From aligning purchase decisions with the business objectives to actually executing the purchase orders with suppliers, a whole host of factors have to be accounted for when planning for a supplier closure.
Download our comprehensive guide to managing suppliers closures:
We cannot ignore it. The complexity of supply chains has increased exponentially in recent years. Whereas once upon a time, a good business strategy alone would be enough to compete, overcoming complexity is now what ultimately sets a business apart from its competitors; a trend which will only become more prevalent in the coming years.
Not only is there an enhanced level of complexity to overcome, but there is also human-factor which comes into play: we want to understand the solutions that are given to us. This is an issue that many managers care about (or at least should care about). “In the past, everything was better”. Well, when it comes to inventory management, that could just be the perfect quote. Of course, simply yelling this out load will not provide a solution.
ABOUT STEVEN PAULY
As a senior consultant and research scientist at Slimstock, Steven Pauly specializes in the mathematical intricacies of inventory optimization. In his role as a consultant, he has been involved in various improvement projects at large companies. Furthermore, Steven is attached to the Slimstock Academy where he offers masterclasses in the field of forecasting and other areas of inventory management.
THE POWER OF MACHINE LEARNING
Over 50 years ago, our understanding of inventory management increased significantly. As businesses realized the enormous return on investment that could be achieved through effective inventory management, this translated into the publication of lots of high-quality literature around the topic.
However, there were no computers back then and solutions were based solely on common sense underpinned by the necessary mathematical analysis. The advantage of this is that solutions were transparent, did not require much effort, provided great insights and were mainly focused on so-called ‘quick wins’. As a manager, you are probably asking yourself: why do anything differently now?
Well, there were many problems back then and more and more continue to arise today. Put simply, solutions based on common sense and mathematical analysis alone no longer suffice.
Perhaps you have heard or read the words: ‘DBC system’, ‘machine learning’, ‘IBM’ and the year ‘1997’ in the same sentence.
IBM’s Deep Blue Chess (DBC) system tells a story that took place in 1997. Through machine learning, they managed to beat the world chess champion. An impressive feat even by today’s standards. The internal employees at IBM boasted that the system understood all possible moves available at any given moment in order to determine the best outcome. This, of course, leans more towards a brute-force approach which makes it especially impressive when you consider the limited computer power that was available at the time.
Yet, there are some snags to this story. Garry Kasparov, the chess champion (or was IBM now the champion?) demanded a rematch. However, IBM refused and the machine was dismantled almost immediately. This, in turn, raised suspicions that Garry Kasparov was cheated by IBM’s Deep Blue Chess (DBC) system.
In 2016, the power of machine learning was once again exhibited. In a strategic game of “Go”, a machine was pitched against another world-champion. Again, the machine was successful!
However, “Go” differs from chess as there are a far greater number of possible combinations. In brief: ‘Go’ has 10^174 possible board configurations. To give you an idea of how this differs from chess: this equates to 1 million, trillion, trillion, trillion more potential combinations.
But what is machine learning? And what makes it different from the brute-force approach or more traditional mathematics? And why and when should we use it? And what exactly do we need to make it work? These are things that management should be shouting about.
First and foremost, is it the learning component of machine learning that separates it from the brute force approach and traditional mathematics. By this, we mean that the machine has the ability to discover relationships and patterns in a data structure without explicitly naming it. It actually learns the ‘rules’ of the problem. This means that solutions can also work in new, unforeseen situations and can tackle problems with high, underlying complexity and a high degree of uncertainty. And that’s exactly where this concept fits into inventory management.
The fact that machine learning differs from other solution approaches creates new, valuable opportunities. Machine learning makes it possible to improve current techniques in, for example, forecasting, but also to tackle a lot of other issues that were not even considered a few years ago. For example, identifying the actual costs if we are unable to deliver an item, or determining when an item is at risk of obsolesce before it even reaches the end of the product lifecycle. Likewise, in production management, latency and machine downtime issues are also in the machine learning queue.
There is no question that machine learning can be very powerful. However, with huge power comes huge responsibility. The main pitfall of machine learning is that for managers, the perquisites are simply not clear.
THE CONDITIONS FOR MACHINE LEARNING
Machine learning is essentially no more than applied mathematics with an emphasis on integrating the current computer power available today. Given the increasing number of potential data sources, coupled with the rapid rate of evolution in computing power, machine learning can be a tremendously powerful tool in inventory control.
Machine learning is statistics on steroids. Yet, it is in essence still “just another tool in the box.” And of course, there are downsides to machine learning. Therefore, it should not become a goal for companies to ‘do’ machine learning.
Machine learning is not a holy grail: it finds its strength in situations where data is abundant but the degree of complexity is so high that traditional mathematics fall short. But exactly how much data are we talking about?
If we have a situation with 5 variables that can each take on 10 different values, then we already have 100,000 possible combinations for the machine to learn. In inventory management, there are often many more variables that can take on multiple values.
If the data is available, machine learning has enormous power. However, in practice, this is the greatest weakness of machine learning. Managers must, therefore, consider how data can be collected in a structured, efficient and ‘clean’ way.
Machine learning also requires a lot of computing power. Some machine learning algorithms are based upon an enormous amount of numerical computations and this can sometimes be a problem in inventory management.
In addition, it is important to keep in mind that solutions in inventory management do not only rely on quantitative results. Ultimately, it is the people who have to understand and work with the solutions. Management therefore has to monitor this closely. As a result, it is important to facilitate knowledge about machine learning and theoretical inventory management across the company.
There are already some cases where machine learning has proven that it can offer a superior solution. For example:
- Optimising promotions policies.
- Achieving the optimal sourcing strategy based on a variety of sourcing options
- Providing more robust forecasting and insight over irregular and new items
There are also projects that are in the pipeline at Slimstock. For example:
- Minimising shrinkage through parameter optimisation, root-cause analysis and pro-active signals
- More efficient management of purchasing behaviour through automatic exception management
- Optimising the service level by determining the actual cost of out-of-stocks
- Achieving a holistic approach to multi-warehouse optimisation
- Minimising obsolete stock through root-cause analysis and pro-active signals
Are you interested in how a machine learning project works in practice? Do you want to know more about machine learning and the techniques behind it? Do you want to gain some first-hand experience in doing it? Keep up with the Slimstock website and our LinkedIn page for latest updates!
COMPLETE THE FORM BELOW TO RECEIVE THE MACHINE LEARNING PDF!
“I need a 100% service level” – a typical expectation of both management and commercial departments. Purchasing & operational divisions, however, have a much better understanding of service levels and appreciate that attaining 100% is a utopia. In practice, determining an appropriate service level is an extremely complicated undertaking.
OPTIMISE YOUR SERVICE LEVELS
For many businesses, the criteria for setting service levels is unclear, and as a consequence, service level targets are configured as a given figure (based on a quick and vague analysis). Furthermore, the quality of the service level is difficult to measure as the effects only emerge after a certain period. It is only when an inappropriate service level has a negative impact on safety stock inventory for example that the service levels are reviewed and quickly adjusted (without any real analysis). Thus, service levels are not evaluated regularly. Should this worry you? Only if you think that service levels are a powerful instrument that has the potential to impact both your profit margins and overall business performance.
Do service levels have such a powerful influence on your margin? And can a well-thought-out service level provide your organization with a valuable asset?
Owning, maintaining, and managing inventory costs a lot of effort and money. However, you need to have enough in stock to deliver customer service: no inventory, no deal.
This paper provides you with the basic knowledge you need for the optimization of your order quantities.
Ordering the right quantities will lower your operational expenses while boosting your return on inventory investment, thereby resulting into an integral optimization of your total supply chain costs.
Working capital fuels your business, but it can be easily eroded. The more inventory you have in stock, the less working capital you have available. Further, the higher the risk that that inventory will become dead stock, meaning it will never contribute to your bottom line at all.
Utilizing a structured approach to your working capital management will help ensure it is well optimized today, and in the future.
Take our 10 question quiz to determine if your supply chain department is effectively managing working capital, and where there are areas for improvement.
It seems that from coast to coast Americans are getting on their bikes in startling numbers. The National Household Travel Survey showed that the number of trips made by bicycle in the U.S. more than doubled from 1.7 billion in 2001 to 4 billion in 2009. Nationwide, the number of people who travelled to work by bike increased roughly 60 percent over the last decade. In another study, the number of bicyclists in the US increased from about 51 million riders in 2012 to slightly more than 66 million riders in 2017.
It is clear that more and more people will start to ditch their cars for bikes as they recognize the many health benefits of cycling and as municipalities continue to support cycling infrastructure.
Omni-channel retailing: a gear shift in complexity
The supply chains that support today’s leading cycling brands have been redefined by changing consumer behavior. E-commerce has many variants and as more and more of us shop online, cycling businesses have had to respond accordingly. Today, even local bicycle shops (LBS) have successfully established an online shop to bolster their existing retail landscape. That said, there are undoubtedly more stand-alone web shops today than there were 5 years ago.
As more and more bicycle businesses continue to explore the ever expanding omni-channel environment, maintaining high levels of availability is now of paramount importance. Given the transparency of pricing on the web, consumer demand in E-tail is far more erratic in comparison to traditional retail outlets. After all, regardless of whether the customer is shopping in store or online, stock-outs directly result in lost sales and disappointed customers. Consequently, businesses must optimize their inventory to ensure the right stock, in the right place, at the right time.
Product lifecycles: the grand fondue
Maintaining consistently high levels of availability across complex product assortments can prove difficult in the best of times. However, in the cycling industry, this challenge is only further exacerbated by the sheer number of new product introductions and ever-shortening product lifecycles.
Simply put, failure to manage product lifecycles effectively can come at great cost to the business: both in terms of lost sales due to poorly introduced new items as well as unnecessarily tying valuable working capital in obsolete stock that won’t sell!
As suppliers further up the chain release new product updates and variations as well as entirely new products lines, retailers have little choice but to add these items to their assortments. Even so, as these assortments grow, businesses must invest in tools and technologies that provide the required insight to make informed inventory decisions. Only then, can business put in place the right strategies to ensure new items are introduced effectively while end-of-life items are phased out with minimal financial impact to the business.
Seasonality: managing the fair-weather cyclist
Inventory challenges are not limited to new product lines and products at the end of the product lifecycle, even mature items can prove problematic. Given that every item is likely to have its own individual seasonal demand profile with different sales peaks throughout the year, business can easily find themselves dangerously exposed to seasonal fluctuations in demand.
For instance, while a long summer is likely to stimulate high demand for new bikes as people make the most of the good weather, a cold snap or a late-arriving spring could seriously hamper sales. Managed effectively, seasonal influxes can provide a welcome boost to sales. Yet, managed badly, these surges in demand can result in high levels of excess stock and, consequently, waste.
As a result, business must remain responsive to seasonal influxes and manage inventory levels accordingly. Through encompassing seasonal uplifts into the demand planning process, business optimize inventory levels before, during and after a season influx.
Outpace the competition with Slim4
Thanks to the accurate analysis and forecasting capabilities of Slimstock's inventory management tool, Slim4, some of the biggest names in cycling rely on our solution to provide supply chain insights to make informed inventory decisions.
With the management by exception principle of Slim4, manufacturers, distributors, traditional retailers and E-tailors can focus their time and attention where it is required most, thus, ensuring planning teams are able to remain more responsive to the challenges presented by the omni-channel environment.
Ultimately, customers of Slimstock can make more intelligent supply chain decisions, respond to seasonal demand and manage product lifecycle: all while maintaining complete control of their entire assortment.
Retailer/ E-tail customers of Slim4 can typically enjoy the following results:
- Up to 30% reduction in inventory sales
- Increased availability across the entire range to over 97%
- Stock-outs reduction of up to 60%
- Greater control over inventory costs
If you want to know more, contact us directly to find out more.
While the sales team may expect consistently high levels of availability in order to satisfy customer demand, the finance team are typically more interested in inventory cost. Consequently, operational teams are under constant pressure to strike the balance between service levels and investment in stock. However, in order to ensure that supply chain decisions are in line with the expectations of the wider business, it is vital that information and insights from across the business are readily available. Yet, despite this, many organisations fail to harness the full potential of internal collaboration.
So what can you do to demolish the internal silos that exist within your organisation? More importantly, how can you lay the foundations to establish more collaborative internal relationships? While inventory management decisions are typically based on rational supply chain data such as historic demand and confirmed orders, for many businesses, there is a strong argument to encompass further insights from finance, sales and marketing teams.
After all, through attaining a greater understanding of customer demand as well as the financial constraints in place, supply chain teams will be able to make better decisions. As a result, the business will become better positioned to guarantee customer satisfaction while still keeping a tight grip on investment in stock and supply chain costs.
As part of our “building blocks to a better supply chain” series, we explore how you can enhance internal collaboration within your organization. This simple 6 step guide will demonstrate how you can gain access to valuable insights from across the business, as well as to rationalize and validate this information. Ultimately, this guide will help you construct a more collaborative environment in which to make more informed supply chain decisions!
Complete the form below to download our simple guide to enhance internal collaboration!