The latest Gartner Hype Cycle for Supply Chain Planning Technologies report predicts that three of the advanced analytic types — predictive, prescriptive and cognitive — are five years to 10 years from mainstream adoption. Other research, such as the Analytics Strategies Study conducted by Supply Chain Insights, shows that 4 percent of respondents have implemented cognitive analytics, with another 15 percent running pilots and 32 percent evaluating its use. There's no doubt that advanced analytics has caught the attention of senior supply chain management practitioners, but most are still kicking tires and trying to figure out the best use cases.
The fact that more than 1,000 supply chain leaders registered to attend a recent webinar conducted by Logility on how to accelerate supply chain performance using advanced analytics demonstrates the mindshare that advanced analytics is receiving. When these 1,000-plus leaders were asked to identify their top business priority, 30 percent cited the need to respond to customer mandates for faster, more accurate and unique fulfillment offerings, and 26 percent said the need to reduce supply chain operating costs. Both of these priorities can be significantly impacted through the adoption of advanced analytics. However, it looks like more than half of all companies still rely on spreadsheets and legacy systems to run and analyze their supply chains.
The adoption of advanced analytics enables many opportunities to lower costs and improve customer service. These include the following:
- Automate routine supply chain decisions to free up resources to focus on value-adding activities.
- Multiply the benefits from investments in integrated supply chain planning and visibility platforms by using this enhanced data to uncover new insights and opportunities.
- Power supply chain optimization efforts.
When asked to identify the top priority for their advanced analytics initiative, the survey revealed:
- 36 percent identify the opportunity to optimize their inventory to balance supply and demand;
- 30 percent highlight the need to respond to customer mandates for faster, more accurate and unique fulfillment;
- 28 percent see the ability to blend data from multiple systems for complete supply chain visibility as a key benefit of an advanced analytics initiative; and
- 19 percent of respondents say they want to leverage machine learning to improve their company’s forecast accuracy.
Applying advanced analytic capabilities to supply chain operations can provide significant advantages in reduced costs, improved efficiencies and enhanced customer service. The goal for most supply chain organizations over the next five years should be to mature their use of analytics and adopt predictive, prescriptive and cognitive analytic capabilities.
So how do you get started on your advanced analytics journey? Take these four steps:
- Evaluate where your supply chain operations lie on the analytics maturity curve.
- Investigate where advanced analytic capabilities could add the most value for your company. What problems can’t you solve today due to a lack of insight or foresight into supply chain operations?
- Evaluate your supply chain planning solutions and develop plans to enhance those solutions, or acquire new solutions that enable predictive, prescriptive and cognitive analytics.
- Learn through piloting an application of advanced analytics in a promising area. Quickly determine whether to implement and/or move on to the next promising area of application.
Henry Canitz is the director of product marketing and business development at Logility, a leading provider of collaborative supply chain optimization and advanced retail planning solutions