Supply chain management is the backbone of a business. Companies in various sectors, from manufacturing to retailing, have increasingly come to realize how much the performance of their supply chain affects their competitive differentiation. These companies understand that an effective supply chain increases their profit level and decreases their operating costs significantly, not to mention ultimately improve customer experience. When markets are in constant flux, companies first seek to optimize their supply chain to effectively utilize their resources and time.
Until recently, Big Data has been making its name as a game changer in the Logistics industry. Big Data has revolutionized business intelligence to a brand new level. By studying a huge amount of data, companies can extract useful information and valuable insights that contribute to a reliable and well thought-out decision-making process. In his ebook “Big Data and Beyond: How Companies Can Find Insight in Big Data,” Vision Critical chief marketing officer Tyler Douglas noted that as much as 65% of global brands embrace big data to stay competitive. What makes Big Data such a driving force before supply chain challenges?
Big Data replaces predictive analytics with prescriptive analytics by providing companies access to a massive quantity of data from varied sources, including suppliers, partners and customers. Analysis of these data using advanced analytical software permits companies to identify complex patterns of consumers’ demand and anticipate potential swings in demand and supply. For example, a cosmetics company can analyze previous transactions and predicts a potential surge in demand. This company can then plan accordingly by increasing its production to avoid lost revenues.
Data-driven supply chain also handles, or at least forecasts, structural shifts in the economy. In this ever evolving world of business, supply chain management can be as complicated as supervising multiple links in a huge chain, from purchasing raw materials, to manufacturing products, to transporting completed items. Above all, we all understand that the failure of one stop means the failure for the whole process. In the face of volatile market, those who are on standby for the changes win the most benefits. By using data to anticipate exceptional events in the market, companies can effectively manage potential risks. With such a risk-minimized plan ahead, they can thus put themselves in a proactive position while making the most profits out of their data-integrated supply chain.
With the help of Abivin vRoute, optimal risk management is no longer a struggle. Abivin vRoute provides stronger analytical dashboards, which include task-based operational reports, single-purposed analytical reports and customized reports. These analytical reports are highly flexible, allowing companies to assess their business health as a big picture and gain thorough insights into their operation while predicting any changes using analysis of historical demand and supply patterns.
2. Saving Time, Reducing Cost
One of the biggest reasons Big Data analytics is worth investing is that it helps companies to outpace their competitors by significantly saving time and reducing costs. Accenture Global Operations Megatrends Study claimed that “Embedding big data analytics in operations leads to a 4.25x improvement in order-to-cycle delivery times, and a 2.6x improvement in supply chain efficiency of 10% or greater.” Data-driven evaluations have now become productive assistants to decision-makers. For instance, before it might take companies hours to come up with an assumingly optimal routing solution, not to mention human errors in evaluating and calculating. Now that Big Data is being exploited using advanced algorithms, companies can implement a solution that is tailored to their own needs and are free of inaccuracies, using Route Optimization algorithm. When an unexpected event takes place, they can re-route in just a couple of minutes, while still being guaranteed that all data are harnessed properly.
Abivin vRoute is a time-saving and economical solution for the Vehicle Routing Problem. By employing Machine Learning that keeps track of historical data and service time data, Abivin vRoute studies past activities and behaviors to be able to improve route optimization over time. Such disruptive feature helps customers to cut down on up to 40% of their logistics costs.
3. Enhancing Performance and Customer Experience
Big Data analytics also contribute greatly to improving companies’ customer service. Big Data analyzes performance of the entire supply chain as a whole, or of separate links in the chain. Should a problem pop up in the process, data integration allows companies to pinpoint the root causes so that they can intervene promptly.
Big Data’s ability to analyze customers’ behaviors and reviews helps companies to understand customers’ experience, thereby making potential changes to improve their performance. SmartData Collective author Larry Alton indicated in his article, “Advanced organizations are using this data to better predict customer needs and preferences, while simultaneously accounting for external factors in the marketplace.” Indeed, integrating Big Data into supply chain management helps companies to delve into customers’ behaviors to understand what they want and – in some cases – even when they want it. This allows them to optimize customer service and noticeably boost customers’ values.