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Supply chains have gone through significant transformation buoyed by the advancement of technology but a lacuna still exists because of the complex structure of supply chains that have hundreds of moving parts. Multiple raw material providers, manufacturers, wholesalers, retailers, aggregators, and logistic solution providers all constitute a complex mix within the supply chain. New-age digital capabilities such as Artificial Intelligence and Machine Learning complimented by progressive data practices can help supply chains overcome complexities but there are factors that call for scrutiny.
A customer-centric supply chain
Everything revolves around the customer. The future scope of supply chains is shaping out to be customer-centric but there has to be data-backed intelligence that defines the relationship between supply chains and customers. Supply chains need to look at data to define their target audience or customers besides evaluating the current standing of the customer in terms of profitability, market reputation, and other factors. A data-driven customer study is also essential to design the relationship between supply chains and the customer, helping supply chains play to their strengths to carve out customized solutions that help the customer grow and supply chains sustain and prosper in the relationship.
Judiciously applying the 80:20 rule
The market is ripe with competition and so is the scenario with opportunities. There are many clients in the market looking for solutions to help them with their supply chain needs. But jumping at every opportunity instead of studying the feasibility of the association, without evaluating the trade-offs or understanding the impact on the market can be futile. Utilizing the time-tested 80:20 rule or Pareto principle that recommends businesses to focus on opportunities that yield significant outcomes can be a safe bet. Using multi-dimensional data backed by technology helps us to look at the holistic picture helping us identify the right opportunities and enabling us to make quick and better decisions. It guides us to associate and align with clients who perfectly fit our priorities, promise the best returns and can optimally benefit from our expertise.
Predicting uncertainty and designing prescriptive measures
Predicting the future is close to impossible but using data expertly can help us predict future scenarios with a fair bit of accuracy. Supply chains looking to stay prepared for uncertainty need to concentrate on two major components. They need to first identify and measure the low probability high impact risks and gain visibility into the probabilities of occurrence and the possible impact it may have. What follows is the prescriptive view or strategy that prepares supply chains for these uncertainties, to minimize the chance of the event occurring or to drastically reduce the impact of the event as and when it occurs.
Exploring varied data sources
Data is undoubtedly the most valuable asset businesses have today though not all data is within reach or resides within the business. The more the merrier is an idiom that perfectly fits the need for more data. But before supply chains set out on the quest for acquiring more data they need to ask a few fundamental questions to ensure their tryst with data ushers’ success. Identifying the precinct behind the need for data and what it will help achieve.
How will sourced data help meet the set goals?
What is the kind of data that I need that is not currently available to me?
In many cases a lot of what we are actively looking for is residing within the business but because it resides in a silo its availability evades our view.
Adopting contemporary technology
Technology is the harbinger of progress and is propelling supply chains to elevate the state of efficiency. While the right use of technologies such as AI/ML can foster speed and scalability, the wrong applications can cripple growth. It is important for supply chains to understand the exact use of new-age technologies and not use it because the world at large is using them. Venture Beat points out that only 13% of AI-driven data-science projects make it to production as businesses assume that throwing in the money and the technology will bring in success.
Embracing Automation
Automation has become a goto solution for supply chains that are reeling due to labor shortages. The pandemic saw many employees pull out of their roles and have since refrained from returning back for their own reasons. The labor shortage has pushed supply chains to reevaluate systems to generate the same throughput without having as many people. Automating tasks and processes that are repetitive and low risk. Data plays a pivotal role here as it helps identify tasks and processes that can be automated and also helps in evaluating the impact of such automation.
Found these excerpts insightful? Tune in to watch our latest webinar titled, ‘Learn How Adopting AI Will Overcome Your Supply Chain Complexities to get an in-depth understanding of the forces at play within and outside of supply chains and how you can maneuver them to your advantage. Listen to Gerardo Pelayo Ph.D., Vice President, Supply Chain Solutions, and Rakesh Prasad, Sr. Vice President, Digital Services share their industry experience that can enable you to navigate supply chain complexities with aplomb.
Associate Vice President – Customer Success
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