Management + Systems

By Nicole Winokur, vice-president of marketing, Optimas

The manufacturing industry has a strong heritage of adopting game changing technologies to deliver higher quality products more efficiently. With the introduction of digital, the industry is moving into an era arguably on par with the industrial revolution.

However, Rome wasn’t built in a day, and digital roadmaps that align with company goals do not take shape overnight. To deliver business transformation, the gap between company goals and digital supply chain strategy needs to close. But how do you get there before the competition?

As supply chain complexity and competition escalate, so do related manufacturing challenges. A few of the most common are:

• The inability to respond to demand variability and intermittent demand: When demand changes faster than a company’s ability to respond, you can end up with the wrong SKU mix and locations, frequent internal inventory transfers and expedites with high freight costs.
• Poor customer service levels: These are manifested by stockouts, incomplete orders, and slow order fill rates, leading to lost sales or missed opportunities.
• Excess and obsolete inventory: Safety stock builds up to cover service level requirements, which can lead to excessive working capital use, carrying costs and internal transfers.

Supply chain planning automation is a way to bring digital strategy to life to mitigate manufacturing supply chain challenges like these that threaten a company’s viability. By digitising supply chain planning users can speed up responsiveness and make smart decisions to cut costs, boost profitability and increase market share.

Optimas is a global industrial distributor and service provider specialising in fastening and supply chain solutions. We embarked on a company wide digital transformation journey to create a stronger, more efficient business. A focus on digitising supply chain planning in partnership with ToolsGroup has helped us better serve each of our stakeholder groups: Manufacturing customers, supplier partners and internal business operations for both our distribution and manufacturing divisions.

Optimas has a ‘long-tail’ of products, which means it has many SKUs with intermittent demand compared to fast movers, as well as highly variable demand. This variability made the SKUs ‘unforecastable’, which caused safety stock increases to achieve service levels. To profitably balance service and inventory, we replaced our intensive, manual reactive planning process with an automated machine learning driven process, to more accurately forecast demand and optimise inventory levels.

With the first phase of implementation complete, we have already seen significant benefits to manufacturing and distribution KPIs, including increased inventory velocity/turns, improved service and reduced stockouts, expedites and on-hand inventory. We are projecting a 60% reduction in inventory across SKUs when the full rollout is complete. Machine learning powered automation has also enabled a 67% improvement in buyer productivity.

For manufacturing customers, we have improved service levels and realised a 7% improvement in forecast accuracy. Improved forecast accuracy means we can provide the same high-levels of service with less inventory.

“ToolsGroup demand planning software enables us to run our operations more efficiently and cost-effectively. With better part level forecast accuracy, we only carry the inventory we need when we need it for our customers, and we’re able to provide our suppliers with a more accurate demand signal. Plus, using this type of digital innovation allows us to attract and retain high calibre talent. Planners are able to work more swiftly and accurately while quickly identifying opportunities for improvement,” commented Kyle Burby, director of supply chain at Optimas.