Data Analytics
Harvest Data Across Supply Chain to Make Money
Can you predict the most popular menu items across upscale restaurants in New York, in the next quarter? Do you know how many fish fillets can be delivered by supplier X next week? Are your fleet maintenance engineers minimizing vehicle downtime by evaluating vehicle repair history and component replacement trends across equipment classes?
Digital technology has radically altered the market dynamics of the food industry. It now offers more choices and enhanced convenience to customers. It allows chefs to personalize the dining experience with insights into tastes and order history. Technology also helps restaurant owners foster customer loyalty by analyzing past behavior including visit patterns, spend on appetizers and beverages, and customer recommendations of a new main course to friends on social media. Most important, it offers real-time visibility into operations and ensures sustainability across functions -optimizes replenishment schedules, enables accurate forecasting to reduce wastage, and shrinks the carbon footprint.
Data tools help food service enterprises simplify operations. Robust data solutions enable the enterprise to become a reliable supply chain partner by connecting data end points and maintaining data quality. A unified ecosystem ensures seamless data flow across the farm-to-fork value chain. Cloud-based platforms use simple protocols for secure exchange of large volumes of data between the ERP, point-of-sale, warehouse, transportation, and inventory management system. In addition, it supports unstructured data from mobile devices, sensors and social platforms.
Scooping insights from data
A well-defined big data strategy converts qualitative and quantitative data into a revenue-generating asset. It helps analysts identify sources of valuable enterprise and third-party information, select tools to enrich primary data, and develop analytical models to gain contextual insights by analyzing data from diverse perspectives. For example, a weather alert can be used to predict the effect on the harvest of a region, sales of supplementary products, and logistics to or from the area.
Big data solutions integrate disparate sources of data into a data lake for real-time analysis and actionable insights that influence business outcomes. Advanced analytical solutions correlate disparate datasets. For example, customized algorithms map a tweet about a snack with socio-demographic attributes of 'followers' and the season to uncover business relationships, this helps in preparing a bottom-up sales plan.
Adopting analytics tools that are ready for innovation
Analytical platforms monetize both big data and granular information. The food map of 'hot-sellers', cuisine, dishes, ingredients, and flavors in a city or community is essential for strategic and operations planning. A drill-down analysis of products, categories, customers, and suppliers ensures the plan is always updated and relevant. For example, an accurate analysis and simulation models can help replace fresh produce with an enhanced frozen version, eliminate an unprofitable non-food supply item, or reallocate a work schedule among warehouse employees. A big data platform automates onboarding of new data streams to address business and regulatory requirements, and incorporates analytical insights into operations.
A self-service analytics tool empowers business analysts and planners, besides others in an enterprise, with a nimble approach to innovate. User-friendly tools can quickly predict scenarios, analyze the root causes of unexpected events, and locate actionable insights.
One of the pre-requisites of a holistic lifestyle is healthy food choices. Just as a diet plan provides data about calories and nutrients that need to be consumed, the food services and logistics industry too needs to harvest data across its supply chain to get lean and fit.
