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Home » Hands Off: iNova Pharmaceuticals Scraps Manual Processes to Improve Planning
Case study

Hands Off: iNova Pharmaceuticals Scraps Manual Processes to Improve Planning

Drugmakers

Glass vials in a pharmaceutical plant. Photo: Shutterstock.

August 8, 2022
SupplyChainBrain

INova’s 500-plus employees deliver a product portfolio spanning weight management; cough, cold and flu treatment; pain management; health supplements; dermatology; sun care and female health products. Under new ownership since 2017, the company has taken steps in recent years to further expand its offerings.

INova knew that achieving its ambitious growth goals meant unifying and synchronizing its approach to supply and demand planning, sales and operations planning (S&OP) and inventory management. Excel-based spreadsheet methods created planning models that differed sharply across geographies, hampering the company’s efforts to promote global sustainability.

“Our business is complex,” says Rowan Seccombe, iNova’s S&OP manager. “In addition to accounting for widely dispersed geographies, our planning processes have to reflect and synthesize different market dynamics. For example, consumer products are promotion-sensitive, and in pharmacy are also driven by ranging and grading. The prescription product portfolio relies heavily on statistical forecasting, a limitation for us in the Excel environment.”

As Seccombe explains, the company’s divergent planning processes hosted in Excel were proving to be a significant impediment to growth, and with continued reliance on manual tasks, the problem would only have grown worse. “Planning in Excel isn’t sustainable due to the personalized nature of the tools used,” he says.

INova turned to a digital supply chain platform from Logility to implement a flexible, “future-proof” technology that could support its expansion plans. Previously, the company had been relying on spreadsheets, integrated enterprise resource planning (ERP) and data warehousing, and a third-party analytics tool to plan and measure its business. These patchwork solutions would be highly inefficient to manage under the best of circumstances, but proved especially challenging given the company’s large geographical footprint, multiple business units and rapid growth.

INova drew on Logility’s integrated set of tools for data management, demand and supply planning, replenishment planning and analytics. What was once a fragmented and time-consuming operating framework became greatly streamlined, enabling cohesive planning across the business and a level of process automation that saved planners time. The use of a statistical forecast allowed iNova to free up resources to concentrate on high-volume and volatile A-class SKUs.

With the Logility digital supply chain platform in place, iNova now enjoys consistency in planning and reporting across all regions. The collaboration has reduced “misfires” and enhanced communication and decision-making across the enterprise. Further efficiencies have been realized as Logility moves iNova away from manual processes and toward greater automation. 

For example, automating purchase order creation between the Logility platform and iNova’s ERP system has resulted in a 40% decrease in manual PO creation, making PO data maintenance far more efficient. In addition, the Logility platform offers user-defined multi-level forecasting, a critical technique for iNova in supporting its S&OP processes, as well figuring out where the business fits within the fast-moving consumer goods (FMCG) sector.

The newfound forecasting capability saves times by automatically updating group-level forecasts when changes are made to individual SKUs, and vice versa. The “pyramid” approach also aggregates demand history into logical groupings, resulting in more stable and accurate statistical forecasts. The results can then be pushed down the pyramid via a “fair-share” method to the item level if needed.

The use of statistical models for forecasting iNova’s relatively stable SKUs has freed up planners’ time to think creatively about managing the more volatile SKUs. The models for the more stable items have reduced demand error by more than 50%, and provided better methods for optimizing safety stocks, the company says.

“We benefited from the industry expertise at Logility, and their local partner Demand Management Systems, as well as the platform,” says Seccombe. “Our implementation consultants constantly challenged us to justify and reconsider current processes, and that was healthy in the end. The implementation went quickly and wasn’t without some challenges, but we’re committed to a journey of incremental improvement and are well supported by Logility to do so.”

Read more: 100 Great Supply Chain Partners of 2022: Weathering the Storm Together

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