Is Supply Chain Analytics The Next Big Thing In Business Intelligence?
In my previous post, I noted the importance of the renaissance of RFID across industry verticals and what this means for pharmaceutical supply chains in terms of elevating their current level of performance. In this post, I want to focus on another emerging supply chain trend that seems to be gaining significant traction by allowing companies to increase operational responsiveness and flexibility. This area, known as supply chain analytics, hopes to allow for supply chains to quantitatively segment multiple data points to make fact based predictive decisions as a means become “data driven” and improve operational performance.
Supply chain analytics, a somewhat nascent yet growing business intelligence platform, led by companies such as Teradata, is proving to be a powerful force. While most companies across industry verticals measure supply chain performance based on what has occurred solely in the past through metrics, this approach will no longer be sustainable in the future. By contrast, analytics ties future and predictive performance together by analyzing trends based on millions of data points gathered from operational transactions in real time throughout the globe.
The idea of analytics utilized within supply chain management becomes even more important as companies look towards cost containment and freeing up working capital, risk management, sustainability, and increased visibility within their supply chains. Therefore, automating the entire supply chain through advanced modeling and predictive performance is not only here for today, but very well may be the way of the future.
The promise of supply chain analytics allows for “intelligent systems” to learn and adapt to how a particular supply chain is run and then make adjustments accordingly through advanced simulation and complex algorithms. For example, this avant-garde system allows for predictive buying and selling patterns (i.e. what is the supply chain impact of a particular promotional event or seasonal trends) to coincide with the proper level of production, inventory, and distribution to more effectively align costs with revenues. In addition, some companies are even using supply chain analytics software as a competitive advantage, to adjust their supply chains based on market conditions, weather patterns, or customer segments. This ultimately provides the correct level of “end to end visibility” of the performance of each specific node within the supply chain in order to improve responsiveness, contain costs, and improve customer service. Sophisticated modeling and analytics software may also allow companies to uncover data that may be overlooked within traditional ERP and CRM systems.
So what does this mean for pharmaceutical supply chains? For one, it can allow for issues and risks to be predicted earlier, such as seasonal spikes in demand and optimizing inventory accordingly. Perhaps this could allow for these supply chains to finally increase inventory turnover and velocity. Or perhaps analytics could provide a catalyst for pharmaceutical companies to predict CMO or supplier performance, allowing pharmaceutical companies to work with their suppliers before problems arise. While this is just a theory the basic premise is sound, using analytics to make precise decisions with greater agility and speed while having a full understanding of why certain events may or may not happen.
Considering that this is still an emerging trend, we would like to know your thoughts on the future of supply chain analytics in the pharmaceutical industry. Is your company currently utilizing analytics to align supply chain goals with corporate objectives? If so, how is supply chain analytics software being incorporated into your existing technological infrastructure?