Importance of Analytics to Drive Decision Making

The first blog in our series on delivering a successful holiday selling season, we emphasized logistics factors in preparing for the holiday season. In this blog we will continue exploring logistics factors influencing preparedness for the holiday selling season.


Success in today’s retail environment requires the ability to measure supply chain performance and feed those insights back into both the executional loop as well as the decision-making process for future investments. Supply chain leaders should consider investing in analytics capabilities that enable data-driven decision making, effective data collection, and powerful visualizations. Investing in analytics can improve planning accuracy, better optimize inventory, reduce transportation and delivery lead times, and build resilience to drive operations consistently and efficiently throughout the year. Analytics, in itself, is not often looked upon to run the business but instead to improve the business and sharpen decision-making through a fact-based approach. Successful analytics capabilities can build dynamic models, leverage the power of data, and present actionable insights:

Build Dynamic Models: In preparing logistics for the holiday selling season, organizations can create and leverage predictive models to reduce costs, improve service levels, better identify demand and establish appropriate inventory strategies. When developing models, first determine the business question to answer. Start with a simple model and build upon that through an iterative approach. Lastly, balance accuracy of the model against deployment of the results: exquisitely accurate models can be very difficult to deploy in real-life – and the goal is to implement quickly to improve business results.

Leverage The Power of Data: Collecting logistics data can be challenging because it can exist in several databases, emails, spreadsheets, and notepads. The holiday season introduces additional data collection challenges for logistics such as temporary storage, processing, and delivery nodes. And all of this data needs to be ingested, cleansed, and curated to feed into the predictive models and drive decision making. This complexity highlights the importance of logistics functions investing in data ingestion, storage, transformation, querying, workspaces, and platforms, as these investments directly translate to the capability of models and the power of analytics and insights.

Present Actionable Insights: Effective decision-making is reliant on how well analyses are presented. Data points can tell a story, but that story may not be sufficient. The ability to visualize & integrate results easily is an important aspect of analytics. Reports & dashboards need to both present the broader picture as well as filter & drill-down to more specific, personalized information for a diverse audience. Above all, the visualization should stay focused on the business problems to answer. Speed to decision, and focus on critical logistics factors, can significantly drive performance and sustain success during the holiday selling period.

Businesses seeking to create a strategic advantage through their logistics operations should consider bold investments in analytics to turn data into insights and insights into actionable decision making. Supply chain leaders able to sense threats, pursue opportunities and quickly react to those threats, at scale, can both achieve better results as well as embed resilience that drives performance in the face of disruption and through all business cycles.