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Inventory optimisation: Minimising risk and waste

Inventory optimisation is the practice of having the right inventory to meet your demand, and buffer against unexpected disruption, while avoiding wasteful surplus. At its best, inventory optimisation is an agile practice that not only responds quickly to risk and opportunity but also has the capacity to predict and prepare for it.

Inventory optimisation is more crucial than ever

As any business leader can tell you, inventory optimisation is a particularly difficult component of supply chain management because it is vulnerable to so many factors, including social trends, natural events, politics, economics, and competition (to name just a few). When the pandemic arrived, it was the mother of all global supply chain disruptions and shone a bright and unwavering light on the volatility of old-school supply chain practices.


Furthermore, when consumer tolerances were for delivery times of a week or more, companies could get by with just a couple of large warehouses. Whereas today, the Amazon Effect sees same-day or next-day delivery becoming an increasing consumer demand. This has had an enormous impact on inventory optimisation because it means businesses now must have multiple distribution centres and require multi-locational inventory management. To top it off, online shopping is at an all-time high and consumer brand loyalty is eroding in the face of increased online choice. This has led to unprecedented levels of competition for many businesses and a shrinking margin for profit and error.

"The supply chain stuff is really tricky."

Elon Musk

The difference between inventory management and inventory optimisation

Both are part of the same inventory-related supply chain operations, but when it comes to defining the specific practices, the overall category is ‘inventory control,’ beneath that lies inventory management and within that lives inventory optimisation.

Inventory optimisation is a key component of inventory controlc

Inventory control encompasses all inventory management operations, including inventory optimisation.

  • Inventory management refers to the goal of setting high productivity and efficiency targets for all inventory operations. Modern business and supply chain planning technologies support these processes by giving supply chain managers greater visibility across all the links in the chain. The Internet of Things (IoT) and cloud-connected devices and assets can be automated for greater efficiency in manufacturing. Production, warehouse, and logistics processes also achieve more efficiency through the application of intelligent technologies like artificial intelligence (AI), machine learning, robotics, and robotic process automation.
  • Inventory optimisation is a subset of inventory management that refers more specifically to profit margins and minimising loss. Carrying surplus inventory causes loss and waste. It takes up space, becomes obsolete, and often doesn’t sell or must be sold at reduced prices. On the other hand, as we saw during the pandemic, shortages and unexpected demand are the flip side of the inventory coin, where the costs come in the form of loss of potential profit and damage to the brand. Therefore, the goal of inventory optimisation is to best forecast demand and maximise the financial output of the inventory for the company.

The different types of inventory

From the consumer’s point of view, inventory primarily consists of finished goods. But for a business, inventory is anything they have to keep in stock, maintain, and replenish. If a company makes soup, then “inventory” could be anything from the seeds used to grow the tomatoes, all the way to the fuel in the company delivery trucks that take it to the grocery store. Looking at inventory management in this more holistic way gives a greater appreciation of its complexity. 


There are four basic inventory types:

  1. Raw materials: All inventory that eventually ends up in the finished product.
  2. Work-in-progress (WIP): As the name implies, this is all the inventory that is currently being prepared and packaged. This is an expensive and risky stage, so inventory optimisation solutions can be applied to help find the most cost- and time-effective processes.
  3. Finished goods: The most commonly perceived meaning of what inventory is, in its packaged ready-to-sell state.
  4. Maintenance, repair, and operating supplies (MRO): All the inventory needed in the manufacturing, production, and delivery of the items. Inventory optimisation is applied to best balance surplus and shortage of these not-for-consumer items.

The challenges of traditional inventory optimisation

Since there have been supply chains and warehouses, one of the greatest challenges to achieving inventory optimisation has been the balancing act between “just enough” and “not too much.” Demand forecasting has traditionally been a backward-looking practice. Even though inventory optimisation and demand forecasting experts are very skilled, there is only so much that human analysis and prediction can accomplish. Therefore, linear supply chains that are powered by legacy systems will always be vulnerable, no matter how much expertise is applied. Some of the most common challenges include:

  • Legacy systems that can neither gather nor manage big data: Manual and non-connected technologies cannot handle volumes of disparate and unstructured data. It is from this data – through the application of smart technologies like AI, machine learning, and advanced analytics – that some of the greatest accuracy is achieved from risk predication to demand forecasting.
  • Fast-moving customer demands: Every year, consumer demand for speedy delivery and customised products is growing. Also, product lifecycles are shorter than ever. It’s expensive for companies to ramp up their logistics and supply chain networks to meet these demands, so greater precision is being asked for from inventory optimisation.  
  • Increased competition: An implication of Industry 4.0 and intelligent, connected supply chain technologies is that businesses can set up and grow faster than ever – all managed from a central hub. This has led to an unprecedented level of competition and consumer choice. Inventory optimisation solutions are increasingly sought after to help provide a competitive edge.
  • Weather events and natural disasters: Every year, we are seeing more debilitating storms and destructive wildfires. Obviously, there is no way to accurately predict such events, but with the use of advanced analytics and cloud-connected solutions, inventory managers can give themselves a fighting chance during the resulting periods of wavering demand.

Building on fundamental inventory optimisation forecasting processes

There is a wide range of inventory optimisation challenges from business to business. For certain seasonal or B2B products, the process may be fairly straightforward, whereas large retailers, for example, may have hundreds or thousands of SKUs and a highly mercurial market and customer base. 


The fundamental practices that underpin inventory optimisation have not changed for decades – even centuries. But, what has changed are software solutions that augment these processes and the specialists who perform them. But even the most sophisticated digital systems are still grounded in many of the familiar and traditional inventory optimisation protocols and formulas:

  • ABC analysis: Identifying the most and least popular products as well as the ones that are most and least profitable. This has traditionally been accomplished through the analysis of past sales data. But with advanced analytics and smart technologies, it’s now possible to better predict trends and anticipate rising and falling inventory needs before they happen.
  • Demand forecasting: Predictive analytics helps anticipate customer demand. It is also used to help predict trends or risks. Again, where this was traditionally a more backward-looping process, inventory management software now allows supply chain managers to minimise the risk of shortages and waste, and more accurately forecast demand. 
  • Materials requirements planning (MRP): A system that handles planning, scheduling, and inventory control for manufacturing. Increasingly, legacy MRP systems are being replaced by integrated business planning systems and demand-driven MRP (DDMRP) systems that deliver greater accuracy and resilience. 
  • Reorder point formula: This reflects the minimum amount of stock before you need to reorder. This has traditionally been a complicated process because it differs from product to product – even within very similar products. For example, white socks and black socks may well have a different reorder point. Inventory optimisation technologies can keep even the most complex multi-locational inventory levels accurate and visible – everywhere and in real time.
  • Perpetual inventory management: This is particularly relevant for fast-moving consumer goods (FMCG) where products move at lightning speed. With smart technologies, perpetual inventory management processes can be fully automated across omnichannel purchasing touchpoints. And machine learning can help these tools get smarter and more accurate over time, even keeping an eye on news, trends, and weather reports to deliver live insights and stock status reporting. 
  • Safety stock and inventory buffers: This is the process of ensuring that there are realistic inventory buffers in case of the unexpected. Since supply chains began, this has been a fundamental challenge because shortages and wastage both lead to a loss of income. Modern supply chain software solutions bring speed, connectivity, and advanced data analysis functions to the inventory management process. This allows businesses to optimise their buffer margins with impressive accuracy.

Inventory optimisation systems: Benefits and outcomes

Historically, the benefits of even small improvements to strategic inventory optimisation could be realised in lowered costs and better profit margins. With the application of integrated business processes and inventory management software, these benefits become more robust and measurable – and only improve over time as the software learns and adapts. 

  • Greater business-wide visibility: The enhanced transparency enabled by inventory optimisation software extends from sales, marketing, and accounting to raw materials suppliers and even global partners, assets, and expenses. Cloud connectivity enables all teams involved in the supply chain to work together in real time.
  • Improved demand forecasting and predictive abilities: Smart technologies can process complex data from sources inside and outside the business – and deliver accurate predictions and insights. When supply chain technologies are powered by AI and machine learning, predictive analytics and demand forecasting become more accurate and insightful.
  • More sophisticated optimisation outcomes: With smart systems that can analyse complex and diverse data sets, inventory managers can see not only which products are the most profitable, but things like which locations are best for which SKU and which combinations of products sell best at different times of the year.
  • Scalability: Companies must scale up quickly for lots of reasons including success and general growth, unexpected events, or seasonality. Smart software and modern databases are infinitely scalable and can ramp up and optimise operations on a global scale.

Going above and beyond with multi-echelon inventory optimisation (MEIO)

Complex (especially global) supply chains benefit from MEIO solutions, which build on the basics of traditional inventory optimisation but use modern supply chain and cloud technologies to get a more centralised, real-time picture of global operations. An effective MEIO solution recommends the optimal inventory levels at each link – or echelon – in the supply chain by simultaneously optimising inventory balance across multiple locations.


With an MEIO approach, manufacturers can analyse demand forecasts with an end-to-end view of the supply chain. And as businesses grapple with the Amazon Effect, MEIO solutions help them cope with today’s more geographically distributed, smaller inventories.

Get started using inventory planning best practices

Modern technologies and smart solutions can deliver enormous benefits to every area of supply chain management, but, in the end, it’s practices and people that run a business. Cloud connectivity helps you connect to your teams and supply chain partners around the world, so put that visibility to work by sharing and rewarding sound practices and efficient inventory planning strategies.

  1. Use robust demand forecasting techniques.
    Demand forecasting is a key factor in informing how businesses strategize inventory management and other processes, such as resource purchasing, inbound logistics, manufacturing, financial planning, and risk assessment.
  2. Make your inventory budget a Q1 priority.
    Every business has cycles and shifts throughout the year. By establishing a quarter-by-quarter inventory budget, supply chain planners can set more realistic and deliverable targets and KPIs.
  3. Implement standard inventory reviewing systems.
    Reviewing systems can be customised for different types of inventory and help to improve efficiency and streamline workflows. It is not uncommon for complex organisations to use different systems within their business. The main point is having consistency and putting a plan in place. There are two main types of inventory reviewing systems:
    • Continuous review system: In this model, the same quantities of items are ordered in each cycle and inventory managers must monitor inventory levels continuously and replenish stocks whenever the quantity of an item drops below a set level. 
    • Periodic review: In this model, inventory managers order products at the same time within each business cycle. At the end of the cycle, necessary stock is ordered based on quality levels at that point in time. This system does not use fixed reorder levels and is more efficient for slower moving products.
  4. Listen to your customers.
    Many businesses only listen to the squeakiest wheels and end up making decisions based upon the loudest feedback. The best inventory management software solutions will be able to regularly gather and analyse data from all your customers and buyers and offer insights and recommendation – in real time – about that input. This helps inventory optimisation efforts by ensuring that inventory management decisions are informed and data-driven.
  5. Use just-in-time (JIT) and on-demand principles.
    Shorter-than-ever product lifecycles and growing consumer demand for speed and personalisation mean that inventory optimisation must be fast-moving and agile. Technologies like 3D printing and robotic automation allow businesses to carry virtual inventories. Supply chain manufacturing and logistics increasingly operate using networks of on-demand providers and suppliers. With intelligent software, inventory managers can make real-time inventory optimisations decisions, confident that the data is backing them up.

Next steps to better inventory planning and optimisation

As with any business transformation, it’s important to establish good communication across your inventory optimisation and supply chain team. Start by breaking down silos, developing strong change management and communication strategies, and talking to your team leaders. Within your workforce is a gold mine of information about current risks and opportunities, which can be leveraged to establish actionable inventory planning and optimisation strategies. Software vendors can also help you develop a road map to get your inventory optimisation journey underway.


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