Kunder forventer, at leverandører kan levere alt, og endda på et øjeblik. Som svar på denne efterspørgsel har mange virksomheder udvidet deres sortimentstrategi for, at omfatte mange tusinder af forskellige SKU'er. Men problemet er bare, at hvor mange af dine varer på lageret har du styr på? Og hvad ved du om dem?
Ved du, hvilke varer der giver det største afkast, eller hvilke der er mest vigtige for dine kunder? Ligeledes, ved du, hvilke varer der koster dig penge?
Selv om udvalget af millioner af forskellige produkter uden tvivl giver kunderne masser af valg, kan det være en konstant kamp at holde trit med disse eksplosive intervaller. Det er trods alt ingen hemmelighed, at 80% af en virksomheds omsætning, typisk genereres af kun 20% af sortimentet.
For at sikre, at sortimentbeslutninger træffes i tråd med både kundens forventninger og kravene fra den bredere forretning, skal virksomhederne sikre, at sortimentstrategien er en klar afspejling af forretningsmæssige mål såvel som kundens forventninger. .
Med dette in mente, hvad kan virksomheder gøre for, at maksimere værdien af deres sortimentstrategi uden at gå på kompromis med deres evne til at imødekomme deres kunders behov? Hvordan kan omdefineringen af din tilgang til sortimentstyring hjælpe med at forbedre effektiviteten af din organisation?
Som en del af vores ”byggesten til en bedre forsyningskæde” -serie, har vi sammensat et værktøjssæt, der hjælper dig med at forbedre din tilgang til lagerstyring.
Udfyld nedenstående formular for at downloade vores enkle guide til bedre sortimentstyring!
When it comes to production planning, there are many factors that influence the overall production plan. Using the growth of the UK bicycle industry as an example, Sam Phipps, explores what challenges manufacturers should prioritise in order to exploit growth and get ahead of the pack.
Bicycle production in the UK has undergone a resurgence in recent years. Since 2007, output has more than doubled and in the last year alone, exports have increased by an impressive 13%. However, UK-based manufacturers have a lot of work to do before they can compete with the Far Eastern powerhouses that dominate the industry. So how can British brands break away from the competition to exploit the accelerating growth in the market?
Boosted by the current buoyant market conditions, all of the major bicycle brands have recently announced plans to achieve substantial growth over the next few years. However, while the current weak pound may have helped manufacturers to increase both output and exports, the good times can not last forever. With Brexit looming, businesses must take steps now to ensure their operation are able to attack the growth opportunities that lie ahead.
Forecasting: maintaining a well-oiled chain
From hubs and spokes to nuts and bolts, even the most basic of bikes are comprised of a vast number of components. While some components are unique to particular products, others are shared across a broad number of products. To add further complexity, consumption rates, minimum order quantities, supplier reliability and most importantly, lead times will differ for each raw and semi-finished component. Consequently, supply chain team’s face a huge challenge in ensuring that every item is available when required!
Regardless of whether a business operates in a make-to-order or a make-to-stock environment, supply chain teams depend on accurate forecasts in order to determine which products to buy in what quantity. Without this insight, operations can quickly become inundated with excess stock as the business invests precious working capital into components and finished goods that simply not required. Or, worse still, the whole operation could become subjected to bottlenecks and delays as the items that are required to meet customer demand are simply not available!
By putting in place tools that enable accurate forecasting, manufacturers can develop robust demand plans which in turn can be used to underpin the entire manufacturing operation. With this additional visibility, supply chain teams can ensure that both the right products are being made but also that all of the required components are ordered at the right time in the optimal quantity.
S&OP: it’s a team sport
When it comes to exploiting growth opportunities, it is evitable that there will always be a degree of risk. After all, to satisfy additional demand, there will be a greater requirement for raw materials, semi-finished components and even finished goods: all of which require investment and tie up invaluable working capital!
However, each business division is likely to have a very different opinion on how this risk should be managed. For example, with the potential to win new customers, sales teams will most likely demand a big investment to ensure that the manufacturer’s operations can keep up with demand. However, on the other hand, finance teams may be more interested in budgetary restraints and thus preventing any financial fallout in the event that growth fails to materialise will be a bigger a priority. Operational and supply chain teams have the difficult task of balancing these perspectives.
In order to synchronise key supply chain decisions around product portfolio management, demand planning & sales forecasting, production planning, inventory & purchase planning, manufacturers must have a well-defined S&OP process in place. However, in order to effectively encompass finance, sales, marketing, and operations teams into the decision-making process, the business must have the required level of knowledge and insight to truly benefit internal collaboration.
Even for the best performing manufacturers, there is always a cap on how much they can actually produce. While the new orders that come with growth will place great strain on operations, by bringing the whole organisation together, a robust S&OP process will ensure everyone is heading in the same direction.
Outpace the competition with Slim4
Thanks to powerful analysis and forecasting capabilities of Slim4, some of the biggest names in cycling have utilised Slimstock's inventory management tool in order to drive the performance of their operations. With a greater overview of the supply chain, OEMs are better positioned to optimise S&OP processes, harness supply chain collaboration and keep stock levels under control. This, in turn, enables supply chain managers to reduce inventory holding and minimise costs while simultaneously maximising service levels and efficiency.
Manufacturers who use Slim4 typically enjoy the following benefits:
- Reduced inventory of raw, part finished & finished good by up to 30%
- Prevent bottle necks through reducing stock-outs by up to 60%
- Greater control over inventory cost
Download our production planning PDF and join our guided expedition around the bicycle industry!
Stock availability: Do you have enough stock to meet demand? Do you have too much? How can you ensure your service level targets satisfy the expectations of the business while still keeping investment in stock under control?
Stock availability is everything for most businesses. However, while the commercial departments within the business may expect 100% stock availability, supply chain leaders understand that this is neither an achievable nor beneficial target to aim for. Given the risk of obsolescence and cost of holding inventory, holding excess stock can have a hugely adverse impact on profit margins as well as unnecessarily tying up valuable working capital.
For many businesses, the criteria for setting service levels is often unclear and as a consequence, service level targets are set 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 of time. It is only when an inappropriate service level has a negative impact on safety stock. For example, that the service levels are reviewed and quickly adjusted (without any real analysis).
Thus, service levels are not reviewed regularly. Should this worry you? Only if you don't think that service levels are a powerful instrument that have the potential to impact both your profit margins and overall business performance.
Download our latest article on stock availability and discover how you could overcome these industry challenges:
- Aligning your service level strategy with the overall goals of the business
- Gaining insight into effectiveness of internal processes
- Establishing meaningful service level targets
Many businesses invest a huge amount of time and effort into developing robust internal processes that secure availability and keep costs under control. While the importance of business rules and internal flows can never be overlooked, business leaders must keep one crucial face in mind: a business is only as strong as its weakest supplier!
To achieve true operational excellence, businesses must look beyond their own operation and strive to build more profitable relationships with suppliers. After all, the performance of your business is hugely dependent on your supplier delivering as agreed.
Once your obsolete stock has been eliminated and your assortment has been optimised, it’s time to kick off the third improvement project. Here, the focus should be on building more profitable relationships with your suppliers. After all, the performance of your business is hugely dependent on your supplier delivering as agreed.
Consider the following observations:
• You order more inventory than necessary because the supplier has a minimum order quantity
• You order additional stock to offset the uncertainty in demand during the long delivery time
• You hold additional safety stock to accommodate for any deviations in the supplier delivery agreement
In all of these scenarios, your business has to make huge investments in stock in order to compensate for poor supplier performance. But is this really the best approach? To help you adopt more effective and collaborative supplier relationships, we have outlined 4 key focus areas to help you optimise your supplier management strategy.
Step 1: Determine your negotiating position
Renegotiating contracts and changing product requirements often depends on both your relationship with the supplier and how dependent the supplier is on you. If for example, an item that you identified through your ABC analysis was an A item for you but only a C item for your supplier, this obviously leaves you in a weak negotiating position. It is also important to know if your suppliers are manufacturing goods just for you or if they supply you from stock.
Step 2: Measure the real performance
An important tool to consider when assessing suppliers is their delivery performance. The most common KPI’s to measure here is the On Time In Full rate (OTIF): what percentage of complete cases are delivered on time?
Additionally, the deviation in actual delivery time is also important to consider: did the order arrive on the agreed delivery date as expected? After all, there is a big difference if the supplier delivers a day earlier or later compared with if the arrival is delayed by several weeks.
Just by measuring the delivery performance of your suppliers, you should see a natural improvement. However, if not, it is time for a stern conversation.
Step 3: Optimise order quantities
In the previous project, we highlighted how you can determine the optimal order quantities. However, in reality, it is not possible to realise these levels if suppliers have in place “strict” minimum order quantities (MOQs). But who actually determines these MOQs? In many cases, a simple call to the supplier will reveal that these are rarely set in stone and may not even be relevant any more. There is always room for negotiation!
Step 4: Sharing Information
Your suppliers can often provide a faster and more reliable service if they know what orders to expect from you. By sharing forecasts, the supplier can better anticipate future demand. There are many advanced technologies for harnessing collaboration. However, simply forwarding an email of the demand forecast can also yield great results!
Download our PDF below!
Slimstock Research Center udfordre konstant grænserne for lagerstyring. Forventningerne til AI & maskine learning er under konstant udvikling, og vores team af eksperter undersøger kontinuerligt, hvordan denne teknologi kan anvendes til at styrke virksomhedernes supply chain.
I dette dokument kigger vi på, hvordan machine learning bliver anvendt indenfor specifikke lagerstyrings dicipliner, med henblik på at udvikle næste generation af ’værktøjer’ som kan styrke den enkelte virksomheds supply chain.
Forecaste efterspørgselen for nye produkter
Nye produkter er notorisk kendt for at være vanskelige at planlægge for. Vores team af forskere undersøger, hvordan machine learning kan udnyttes til at fjerne usikkerheden og risikoen ved nye produktlanceringer. Gennem anvendelse af machine learning algoritmer med avanceret konfiguration vil AI-baserede systemer klynge efterspørgselshistorik fra flere produkter, med det formål at identificere og forudse trends i efterspørgslen. Dette vil igen gøre det muligt for systemet at forudse mængden af efterspørgselen. Resultat: Supply chain teams vil være i stand til at bygge robuste prognoser for nye produkter, langt hurtigere end ethvert eksisterende værktøj, som i dag er til rådighed!
”At sælge eller ikke at sælge”
Hvordan kan du afgøre, om din nye produktlancering har været en succes eller ej? Eller endnu vigtigere, hvordan kan du bestemme, om et nyt produkt skal fortsætte eller aflives efter lanceringsfasen? Ved at udnytte specialiserede produktkategorier kombineret med machine learning algoritmer og avancerede matematiske teknikker, undersøger Slimstock Research Center, hvordan machine learning teknikker kan hjælpe virksomheder med at foretage mere proaktive beslutninger i forhold til lagerets sammensætning. Desuden er vores team ved at udvikle et system til at identificere den rigtige salgspris på en lagerført vare, således at produktet genererer overskud.
Identificering af afvigelser
Ved at benytte teknikker lig dem, der er anvendes til identificering af svindel, så bruger vores team machine learning teknikker, der gør det muligt for supply chains at identificere afvigelser i efterspørgselshistorikken og eventuelt udelukke disse fra enhver analyse. Ved at benytte avancerede neurale netværk til klynge SKU numre, der er stærkt følsomme overfor afvigelser, så vil man kunne håndtere disse produkter mere proaktivt.
Denne udvikling vil betyde at man kan opdage uregelmæssigheder i den daglige drift som f.eks. kundetransaktioner, tilgængelighed og lagerstatus. Som resultat heraf vil pålideligheden af både processer og beregninger blive drastisk forbedret!
Minimering af spild er en kompleks udfordring! Eftersom spild kan skyldes flere faktorer, er Slimstock Research Center i gang med at udvikle værktøjer, som hjælper virksomheder med at forudse niveauer for spild, og i mødegå årsagerne. Ved at fokusere på den optimale ordremængde for varer med begrænset holdbarhed, og varer der har stor risoko for at blive forældet hen i mod slutningen af dets livscyklus, undersøger vores team, hvordan AI kan hjælpe forsyningskæden til at få større kontrol over spild.
Optimering af kampagner
Resultatet af kampagner kan være svære at forudse, men efterhånden som løsninger indenfor AI bliver bedre, vil vores team af forskere konstant forsøge at være på forkant med hvordan sådanne teknologier kan udnyttes til at optimere processen omkring kampagner. Ved hjælp af en teknik kaldet 'deep reinforcement learning' undersøger Slimstock Research Center aktivt, hvordan denne teknik kan udnyttes til at hjælpe virksomheder med at udvikle mere effektive kampagnepolitikker.
Download denne info. side om Slimstock og AI nu!
With a baby on the way, it’s always an exciting time. However, here at Slimstock, we understand how challenging it can be to find effective Maternity Cover. Even when you do find the right person, it still takes time to bring that person up to speed with your business processes.
To keep your business on track, Slimstock can offer your team an experienced consultant to support your operation throughout the maternity period. With their extensive knowledge of Slim4 coupled with their industry expertise, our consultants can help you continue your optimisation efforts until your team member returns.
From helping to drive your inventory projects forwards to improving and advancing the knowledge of your team, a bespoke project can be agreed according to your specific business requirements.
Prices are available upon on application.
Excess stock: we all know that holding too much is bad for business. Yet, based on the experience of the inventory analysts as Slimstock, of all the items in your warehouse, typically, 10% will never be sold. As these items become obsolete, they can cost you a lot of money and needlessly occupy valuable warehouse space. Given that such items are unlikely to bring in any revenue, why are you holding on to them?
Eliminating excess stock takes great courage!
The problem is removing these items from your operation is often easier said than done. Given that you have made a financial investment in these products, accepting that these items no longer offer any value can be a hard pill to swallow.
Although writing off inventory will come at the cost of your margins which won’t amuse the finance director or the board, it is totally necessary. After all, when you consider that you have already lost your original investment in these items, continuing to hold on to excess stock will only cost you more money!
“Painlessly” remove excess stock
So, what can you do to eradicate surplus inventory from your operations while still keeping the potential financial impact to a minimum?
We have outlined 4 simple steps to help you eliminate the excess stock which is holding your business back. Through following these tips, you will be able to minimise inventory costs and free up working capital: both of which will no doubt be music to the financial director’s ears!
Step 1: Physically remove the stock
The first step in managing obsolete stock is to physically remove these from your warehouse and store them in a place where nobody will find them. You could store them in a container or even bury them; doesn’t matter so long as it’s out of sight. Although this may seem like a bold move to effectively “hide” obsolete stock, this is completely necessary. After all, these items are already costing you too much money and for as long as they are in the warehouse, they are nothing more than a distraction which takes up valuable space that could be used by items that actually make the business money.
Step 2: Remove from the administrative process
Once you have identified the excess stock, the last thing you want to do is order even more! Ensure that the obsolete articles are removed from your ERP as well as any other transaction system. If that’s not possible, at the very least make sure that purchase and sales orders for such items can no longer be placed.
Step 3: Financial devaluation
And then comes the hardest (yet unavoidable) step: re-valuation of the stock. Although painful, you cannot afford to postpone this step. If you do, sooner or later you have to go back to the same old conversations with your sales and finance colleagues. And as stated earlier: obsolete stock won’t yield anything so only costs the business more and more.
Step 4: Damage control
The excess stock has now been declared are now ready for destruction. However, if someone is prepared to buy up the stock, then, of course, this is beneficial. Perhaps a buyer is interested or maybe you can ask your supplier to take their old stock back. Another idea is to identify the last customer who made an order and make him an offer he can’t refuse.
You might be asking yourself at this point: why not take these actions while the stock is still in the warehouse? However, based on experience, this can often mean that the obsolete stock remains on your balance sheet at the end of the year!
Prevention is the best cure
After going through the painful task of removing your existing excess stock, the last thing you want to do is to go through the same process again in 6 months’ time. Focusing on optimising stocking policies, services levels and product lifecycles, we help hundreds of businesses just like yours to put in place the right processes, tools and knowledge to minimise the risk of excess!
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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 specialises in the mathematical intricacies of inventory optimisation. 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 realised the enormous return on investment that could be achieved through effective inventory management, this translated into the publication of lots of highquality 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 bruteforce 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!
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UNRAVELING THE SECRET OF OPTIMAL ORDER QUANTITIES
Whether it consists of raw materials or end-products: inventory is unavoidably one of the largest single assets on your balance sheet. In the manufacturing industry, around 37% of total costs consist of inventory costs, while for retailers and wholesalers even more than half of the total costs are caused by inventory. 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 discusses an indispensable inventory management figure: the economic order quantity.
Download or EOQ pdf! this PDF will provide you with the basic knowledge you need for the optimisation of your order quantities. Now is time to put it into practice!
Is your business holding too much stock? In a bid to keep customers happy, many businesses have resorting to offering high levels of inventory across already spiralling assortments. While this ensures that customers have plenty of choice, keeping up with these exploding ranges can prove a constant battle. What steps can building businesses take to overcome these inventory challenges?
How much stock is too much stock?
The honest answer for many businesses is that they simply do not know!
In pursuit of a unique selling point, many businesses have developed extensive assortments encompassing many thousands of SKUs. However, managing such a large number of items brings with it its own range of challenges.
No doubt many business will be all too familiar with consequences of holding too much stock for some products while others are left dangerously exposed to stock-outs!
How can you optimise inventory levels across your long tail products?
80% of a business’s turnover is typically generated by just 20% of the assortment. Yet, many businesses invest a huge amount of resources into managing thousands of items that offer limited value to the business while ignoring those that matter to the customer. The reality for many businesses is that they hold too much stock for the wrong products.
From service levels to stocking decisions, an effective ABC analysis can provide the essential insights required to shape the assortment and help make informed decisions.
In our latest article, we explore 3 top tips you can adopt today to help reduce inventory levels, improve cash flow and help maximise the profitability of your long tail.
Download our guide to adopt a more tailored approach to manage your long-tail assortment.
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