Despite of robust sales and a long, successful business history in the field of veterinary drugs manufacturing, a lack of attention on analyzing supply and demand of its products threatened the organization to lower its market share. Leadership of the company turned to Research Nester to help find them a solution to support their continued growth.
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A leading veterinary drug manufacturing company from the United States, who already had a strong hold of its market share, backed by its long-running successful business history, had experienced a major set-back when it found losing out on its existing market share.
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The organization had the goal to increase its market share by further 5% by the end of 2035, and position itself as the highest share holding player in its arena.
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Research Nester offered its supply and demand analytical research solution, which is based upon its unique ‘Nest-omics’ model, helped the company analyze effectively the supply and demand of its veterinary drugs and animal vaccines and bridge its supply chain gap.
The COVID-19 pandemic, which shook the world globally in the year 2020, claiming 6908554 deaths till April 19th, 2023, had a dramatic effect on the demand and supply of products, thereby significantly disrupting the supply chain of businesses. Focus of the organization on developing vaccines for COVID-19, had a severe downturn on veterinary drug product line. Research Nester’s analysts observed that during the year 2020, about 15% of businesses in the healthcare industry had lost of over USD 500 million, while around 35% and 19% of businesses recorded losses between USD 60 and 100 Million, and between USD 100 and 500 Million respectively. Our estimates also suggest that within the next 10 years, supply chain disruptions would tally to around 49% of the profit generated in a year for business organizations. Unlike other businesses that were impacted as a result of COVID-19, the leading veterinary drug manufacturing company also experienced stern fluctuations in the demand and supply of their drugs and vaccines. These impacts were continuing since then and were hampering the market share of the organization. Lately, when the veterinary drug manufacturing company experienced this major set-back, it requested Research Nester to act on its behalf to find out a solution for the problem. The team of consultants and analysts at Research Nester found out that the organization missed out on the following major areas:
Unlike other scenarios, Research Nester used its unique 3-stage CDG analytical model, which focuses on understanding the current state of the client, the desired state which the client expects to reach, and therefore the gap between these two states that is present. The gap analysis helped our team to understand that the company spent huge cost on managing its inventory due to poor supply chain, lacked by a proper information on the demand and supply of its products. The veterinary drug manufacturing company was offered a customized solution on supply chain analytics which would help the organization in bridging its logistics gap by focusing on mitigating risks associated with the entire process. By utilizing these analytical tools, our client was able to enhance its on-time in-full (OTIF) delivery performance as well customer satisfaction, and also optimize its inventory. All of these contributed to a maximize in its revenue. Some of the major areas wherein our client was requested to enhance its focus were:
Utilizing the unique ‘Nest-omics’ model, Research Nester could understand the average market demand of the company’s array of products, which majorly included veterinary drugs and animal vaccines. This helped the company to develop effective supply chain strategies and optimize processes, leading the company to deliver an increase in market share to 59.58% during CY2022 from its pre-recorded share of 56.61% in CY2021, an increase of about 5% between these two years. The company also lowered about 80% of its back-order risk, decreased around 55% in variability, and reduced close to 40% in lead time.
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