nVentic helped a manufacturer identify double-digit improvements. We also quantified the impact of existing constraints through process industry inventory optimization.
Context
Our client was a manufacturer of high-quality material solutions in a very competitive market. To deal with their competitive landscape, they had successfully driven down production unit costs. However, their production schedule was constantly running at or near capacity. This created a surplus of inventory. Challenges with service level had only recently been addressed to bring them close to target.
Production and supply planning were done manually. Important ERP fields such as lead time and Minimum Order Quantity (MOQ) were left blank. This was a barrier to automation. Because the most important raw materials were chemicals, the system used backflushing to record raw material consumption based on the bill of materials. This is a classic challenge in process industry inventory optimization.
Approach
nVentic’s standard Inventory Evaluation faced a number of challenges due to the data. Backflushing was causing significant negative balances in WIP but as the overall value was low, we decided to exclude it. We worked with local planning teams to derive good, conservative estimates for lead times as well as the MOQ’s actually in use, which were very significant. These data inputs were collated with other master data and all transactional data directly from the ERP. Service levels were set very high to account for late delivery penalties agreed with customers.
Because the MOQ’s were very high compared to average demand, nVentic also carried out sensitivity analysis to quantify the impact of those MOQ’s on inventory levels precisely. This then allowed our client to reassess their production constraints in light of the impact on working capital.
Results
nVentic’s Evaluation, even with the full constraints applied, identified a reduction potential of over 20% while improving service levels fully to their target levels. Moreover, our sensitivity analysis demonstrated that the MOQ’s applied by Production to maximise their output KPI’s more than doubled the overall inventory requirements. Reducing batch sizes allowed more products to be manufactured each week. This reduced inventory requirements while improving responsiveness to changes in demand.
Our work in master data also allowed bulk uploads of validated critical data to the ERP, which allowed the client to move towards a digital transformation in planning technology
nVentic helped an industrial manufacturer reduce shortages and excesses at the same time. We identified a 45% reduction in inventories while improving service levels from 85% to 99%.
Context
Our client was an industrial manufacturing firm with a high number of SKU’s. They had problematic data quality, and a desire to improve fill rates as well as reduce working capital.
A major challenge facing the client were capacity constraints – often inventory was moved between locations purely for want of space. This added superfluous stock movements to the data (not to mention logistics and handling costs).
Approach
nVentic evaluated the client’s 7 principal sites, working with a small central team in the first instance. Efforts needed to be put into data preparation, because of a number of challenges, especially a fragmented and incomplete material master.
First sight of the data also highlighted an unusual problem – multiple items were showing negative stock levels! We decided not to correct the negative stocks to maintain data integrity and highlight the scale of the problem. We also set target service levels at 99% to help the client identify opportunities to reduce shortages as well as excesses.
Early on, nVentic recommended process improvements that would be beneficial in their own right, as well as improving data quality. The negative stock issue was caused by gaps in the booking process. We also recommended a rationalisation in the number of SKU’s. The client was already aware of the issues around capacity constraints and wasteful stock movements. They needed help to free up space while improving fill rates and this is where nVentic’s Inventory Evaluation was invaluable.
Results
Despite the challenges, we identified an overall reduction potential of 45%. Using nVentic’s clear and simple to follow evaluation, the client decided to set a target for the first 3 months of 25% and to focus on the 500 SKU’s with the greatest improvement potential. Given the quality of the underlying data, checks were done on all key parameters (such as lead time) for each SKU before implementing changes. Planners then bridged the gap between our recommended levels and existing levels stepwise, so that they could further minimize risks caused by data inaccuracy.
The client targeted the SKU’s with the greatest risk of shortage and built up enough stocks to improve service levels. The outputs of our evaluation provided the full planning team with a 6 month action plan. It was immediately apparent that during that time a major improvement in inventory levels could be realised. Refreshes of nVentic’s Inventory Evaluation every 6 to 12 months allowed benefits to be sustained.
Automotive inventory can be challenging to optimize since just-in-time logistics has long been a favoured principle, especially for the OEM’s. However, nVentic demonstrated how even a best-in-class operation still had double-digit improvement potential.
Context
Our client was a major OEM manufacturer in the automotive industry. Globally, the company demonstrated average performance when benchmarked with its peers for DIO. However, nVentic was invited to look at their flagship site, where they believed performance to be best in class. Having already been through several projects to improve inventory management, the client still struggled with inventory performance visibility and asked nVentic to run a proof of concept project.
Approach
nVentic immediately understood why inventory visibility was poor. The 6 million transactions per year were deleted from the ERP systems and warehoused on a frequent basis. We therefore had to deal with multiple instances of missing or conflicting data right from the start. Rather than wait until all data was available, we focused on what was immediately to hand and carried out our standard Inventory Evaluation on that basis.
Results
Despite the client’s expectation that we would find little or no improvement potential, nVentic identified an overall opportunity to reduce inventory by 15%. Around 5% was identified in finished goods and 20% in raw materials. The client commented that the transparency we gave them in a week was something they had failed to achieve for many years. We also made some key recommendations in master data management. Automotive inventory may be lean compared to other industries, but that doesn’t mean it is as close to optimal as possible.
Would you like to talk to one of our experts? Contact us
This major industrial manufacturing company asked nVentic to help them with inventory optimization. Their inventories increased and decreased over time depending on senior management focus and pressure. To get past this, the client wanted a sustainable solution to keep inventories balanced.
Approach
nVentic mapped the internal supply chain flows and helped the client extract the relevant reports from their system. We then transformed and analysed the data and identified an initial improvement potential of more than 25% net. This took account of some SKU’s where a shortage of stock was identified. nVentic categorized parts based on value/volume and variability. We also graphed historical stock evolution by SKU. Using nVentic’s proprietary tools this took just a day, from receiving the data to producing the report.
Client project teams were set up to agree the approach and lead workstreams. A baseline was set and a tracking mechanism defined. Quick wins delivered a 10% reduction of excess stock in only 3 months.
For the initial phase, top-running SKU’s were targeted. Improvements in key data quality were implemented. Improvements were also embedded in the underlying processes. Weekly tracking of KPI’s and stock position by SKU were set up to enable an ongoing focus and transparency. Production and storage strategies were reviewed for all parts.
Inventory optimization is always useful for industrial manufacturing companies. Having achieved the first-year target of a 25% reduction in inventory, a target of a further 20% was set for the following year, and further projects scoped out to deliver it.
Results
Inventory was reduced by more than 50% from the initial baseline over a period of 3 years, while service levels were maintained or improved. Improvements in the underlying data led to a better understanding of how and why to act – inventory optimization capability was significantly developed within the client’s teams.
There is still strong potential to take out more than an additional 20%, as well as to widen the scope. nVentic continues to support this client.
nVentic helped an industrial manufacturing client sustain substantial 2019 gains in inventory optimization through the 2020 pandemic.
Context – Coronavirus pandemic
Ways of working were put in place to deliver sustainable performance and continuous improvement in inventory management.
Towards the end of 2019, a further net reduction potential of 15% was identified and action plans put together.
Early in 2020, however, the global pandemic created additional supply chain challenges:
- Demand patterns changed, with a softening in sales
- Delivery concerns arose for a number of critical suppliers
- Production was disrupted, with stoppages in several manufacturing countries
Approach
nVentic’s analytics and consulting support helped the client to take appropriate mitigation actions without losing focus on the longer-term improvements in inventory management. Key to achieving this was balancing objectives and careful data analysis to reach the best balance:
- As soon as the impact of the pandemic was anticipated, critical suppliers were identified and strategic additional buffers of stock planned and built where necessary
- The net impact of the additional buffers on the overall annual target was calculated and detailed plans updated
Each site was responsible for identifying and implementing actions to achieve the targets.
Programme management was coordinated centrally, with standardised reporting. We supported global steering and provided analytics, as well as supporting manufacturing sites facing particular challenges.
One of the primary challenges, especially in the early phase of the pandemic, was in establishing and maintaining transparency.
A number of supply issues were combined with a slowing in demand and it was essential to understand and prioritise the risks so that additional stock could be built where needed without losing pressure and focus on the underlying improvements planned.
nVentic carried out a number of analyses, applying statistical techniques to provide rapid insight and focus. We also worked with local teams to enable them to understand and take full advantage of the data insights provided.
While the early part of the year, especially the second quarter, was primarily concerned with preserving supply chain resilience, by mid-year the situation was clear and improvements were driven through in the second half of the year.
Results
Compared to the initial target of 15% net reduction, 12% was delivered, with the 3% delta caused by the additional stock deliberately built to offset Coronavirus risks.
Service levels continued at their baseline high levels and no more sales were lost through lack of inventory than prior to the programme beginning in 2019. Further reductions have been planned for 2021.
Would you like to talk to one of our experts? Contact us
Context
Our client was a global manufacturer with a broad range of products, both make to order and make to stock. The company was engaged on a drive to reduce inventories in order to free up working capital, but did not want to sacrifice growth or customer service. They wanted to optimize inventories but were concerned about supply disruption caused by various supply chain issues.
nVentic carried out inventory evaluations to quantify and target reductions while slightly improving service levels. The baseline service level % was in the high 90s. However, there were two major externalities to manage:
- The client was going through a brand switch at some of its main sites. The old brand was being phased out and a new brand phased in. This needed managing very closely to minimize obsolescence while not damaging the introduction of the new brand
- Severe disruptions amongst the supply base had led to shortages the previous year and safety stocks had been built
A high percentage of raw materials came from Asia and average lead times were 3 months.
Approach
nVentic’s analytics and consulting support helped the client to right size inventories in the face of significant uncertainty. Key to achieving this was ongoing sensing of demand:
- We helped the client to decouple forecasts where appropriate. For around two thirds of items, historical demand was a poor guide to demand, while sales forecasts had systematic bias. Widespread use of deterministic planning meant that forecasts were being turned into fixed orders before planners could react
- Sensitivity analysis was carried out to model different degrees of variability and the impact of specific scenarios such as supplier failure and lead time increases
- To keep planners comfortable that supply disruption would not be a problem, we took a conservative approach to lead time variability by selecting maximum lead times for all items and updating target safety stock levels on that basis. We also helped them assess the data quality within SAP and quickly take appropriate action to update key parameters like lead times within the system
- On a weekly basis, forecasts and orders were updated based on the latest information
At the heart of the modelling was predictive analytics. The first stage of this was done using a number of standard reports from SAP:
- Stock reports
- PO lists to show items on order along with expected delivery dates
- Forecasts
nVentic created a report to predict stock levels for the coming 6 months. This predictive report was given to planning teams weekly, allowing them to layer on known externalities (i.e. all information not within SAP).
The granularity and flexibility of the data reports made it very easy for planners to foresee shortages and overstock positions, and so update plans and orders.
Results
nVentic helped our client segment the data to target additional safety stocks only for those suppliers who genuinely represented additional risk. This alone allowed safety stocks to be greatly reduced.
Specific mitigation plans were put in place to deal with the actual supply disruption, including strategic building of inventories for some items and the sourcing of alternative suppliers.
A good deal of attention was also put on cycle stock. At the start of the project, a lot of planning was done manually and orders placed with set cadences – monthly or weekly – based primarily on planners’ bandwidth. nVentic’s analysis allowed the client to see how much benefit could come from shortening order cycles for certain items. This better smoothed demand to suppliers and helped reduce upstream variability, as well as reducing cycle stocks.
Perhaps the biggest impact was achieved by giving planners forward visibility of predicted stock levels. All of the data they required was in SAP, but previously they did not have the means to extract it and manipulate it in a timely manner.
In addition, new techniques were introduced to the planners. There had previously been an excessive reliance on a small number of MRP types in SAP. nVentic helped the planners to understand where to apply different MRP types. This facilitated greater automation for some items, giving planners more time to deal with the more difficult items.
Using the predictive analytics, the client delivered a 20% decrease in inventories in one year, while improving fill rates. Furthermore, much greater transparency was created, with planners having a much better idea what future inventory levels would be. At the end of the year a further 15% improvement potential was identified by the planning team itself.
Would you like to talk to one of our experts? Contact us
Our manufacturing client had a particular challenge with sporadic demand for a high number of items.
Context
nVentic were asked to analyse the demand for these items and to identify an approach to manage them that would deliver an improvement in performance and also be pragmatic – compatible with existing technology and with clear criteria for planners to follow.
3 approaches were considered:
- Deterministic planning, allowing planners to fix orders based on their experience and knowledge
- Plan to forecast, tying orders to the forecast
- Replenishment, setting re-order points
Approach 3 was tested using 6 different statistical approaches.
A range of other levers were also considered, including reducing lead times, reducing minimum order quantities, reducing batch sizes, increasing review frequency, shaping usage, varying service levels, and updating policies.
A dozen criteria were identified to segment items appropriately.
nVentic identified for the client which items should follow each of the 3 approaches. Through testing, we then identified appropriate statistical distributions to support the replenishment approach. An assumption of normal distribution underlies a lot of inventory management technology but this is particularly problematic with sporadic demand.
Results
Our analysis found that two thirds of the sporadics considered would benefit from a different approach, which could be managed using their existing technology. The high service levels could be maintained while reducing inventory levels by 17% overall.
The remaining third had extremely sporadic demand (no demand at all for 9 consecutive months). For these items alternative strategies, like increasing customer lead times or finding alternative sources of supply, were the only option.
We found that Forecast Value Added (FVA) was too low for most items to make option 2 a viable alternative. Replenishment was the best option for a significant percentage of items, but it was essential to factor the high variability and sporadicity into considerations of safety stock and re-order level. It is also essential to understand that the segmentation is not static and that the client needs to refresh the analysis regularly to take account of changes in demand.
Would you like to talk to one of our experts? Contact us