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Supply chain solutions: 3 industry challenges big data can tackle
The cost of consumer acquisition and relationship management is too high. Government regulations are overbearing. Top talent is tough to find. These were some of the most prevalent challenges reported in a 2015 survey from Material Handing and Logistics (MH&L).
Today's consumer packaged goods (CPG) industry leaders are tackling these pain points head-on with supply chain solutions that utilize data. Thanks to new analytics technologies, organizations have the potential to improve efficiencies, increase speed to reach consumers, build predictive models and provide customization at scale. To get there, supply chain managers have faced some big challenges over the last 10 years. Here are three that big data has helped combat:
Consumer demands for better-tailored inventory
As supply chain consultant Jim Tompkins points out in Supply Chain 24/7, retailers want to reduce the number of vendors with whom they are working. Simultaneously, they want to devote their time and attention to those manufacturers that can offer the greatest product depth and variety. Meanwhile, consumers want products and marketing messages that are tailored to their exact buying intentions and needs.
Effective big data analytics can help. Tompkins explains that supply chain leaders are tackling these challenges by functioning as marketplaces. Rather than stocking inventory, companies can pass orders on to marketplace partners. With big data as a guide, industry leaders can develop consumer relationship management and product inventory integrations to simplify this process.
Process automation as a strategic opportunity
Automation is a top strategic priority for supply chain leaders. By eliminating redundancies and reducing opportunities for human error, organizations are better positioned to reduce costs while increasing the speed of delivery. Organizations need a mechanism to identify bottlenecks, pain points and opportunities for greater efficiency.
Until recently, supply chain leaders have been developing these analyses with a piecemeal approach. Without a global view of their processes, companies can face challenges when addressing all business objectives concurrently and equally. Data plays an important role in providing the transparency necessary for a holistic planning process. Important metrics to monitor include manufacturing time, production cost, retailer engagement and transportation efficiency. By automating these efforts, supply chain leaders can create a continuous stream of necessary information to benefit their overall strategy.
Simplifying complexities
What organizations need are supply chain solutions that target microdecisions and micromoments. That's where big data enters the picture: Supply chain leaders can fine-tune their production and logistical networks by increasing their reliance on data processing and analytics tools. The biggest opportunities exist in real-time supply planning, dynamic data feeds and preventative maintenance. Companies can use data to visualize delivery routes, forecast future demand and create straightforward distribution networks.
Big data introduces new opportunities to the supply chain industry, but the road to implementation will be a long one. When it comes to analytics and consumer intelligence, many organizations are just scratching the surface. Those who take advantage of this early market opportunity will be best positioned for the long haul.
The supply chain industry is undergoing substantial change, and organizations need a way to make informed decisions while minimizing risks. Big data and analytics can help. Instead of launching new initiatives based on assumptions, organizations can take calculated steps based on predictions of what is likely to perform well in the market. Big data adds value to brands' focus on consumers and the ability to achieve results without breaking the bank.
How do you use big data to predict demand and streamline planning? For real, actionable insight, visit our Consumer Products Solutions page.
