Your supply chain analytics go a long way toward optimizing your company’s global supply chain. Still, you need a sophisticated digital model to tap the correct data from Internet of Things (IoT) sensors, the Internet, retail and e-commerce register receipts and the growing Metaverse. With this analytical model constructed, you can leverage a proactive approach using predictive analytics.
Creating a business that succeeds involves fostering a decision-making process that enables the organization to make solution-centric decisions. It’s a move away from a hierarchal process to one that places decision-making in the trenches of the day-to-day work, creates an organizational structure that eliminates information silos and shares decision-making with the most experienced, informed employees. How do you do this?
Everyone talks about big data, but volumes of data that do not provide insights do not help your business. You need to blend your source data creating meaningful, usable information, which can be visualized into actionable insights that provide value to your business.
Analyzing your supply chain can help streamline processes and simplify acquisitions, but it also helps identify and eliminate waste, manages cashflow and uncovers risk patterns.
The manufacturing industry and field service industry are facing a growing problem – how to capture tribal knowledge from an aging population of workers. At the 2019 Field Service Conference in Amelia Island, FL, this topic was widely discussed amongst industry representatives.
By: Dmitriy
When most people think of ML, they imagine a team of data scientists, high overhead costs for computer hardware and timelines that stretch into quarters or a year before seeing results. But today the market is filled with automation tools and cloud-based computing power. ML, AI, and Big Data are available more than ever. It is now easier for medium to large-size businesses to start using and applying these advancements in business intelligence technology to grow and improve their business.
One of the things I enjoy about our work in analytics is the variety of business problems we solve. While the specifics of the problem vary, our overall objective is always to derive value from the data. Putting the client’s needs first means that we adjust our approach to best fit the situation rather than fixate on a specific tool or pre-selected solution. This variety makes the work exciting, but it also creates challenges in staffing the appropriate skills. Over the years, I have come to refer to our solution to this challenge with the phrase “Analytics is a team sport.”
The term predictive analytics refers to the analysis of existing data to create forecasts that when properly applied, help avoid future problems. While kaizen helps spot problems live on the manufacturing floor, using predictive understanding methods provides an opportunity to:
There’s a reason why businesses are trending towards big data. Data analytics can be used to isolate areas of a business that need to be improved, in addition to paring down to the areas of the business that are performing most successfully. Through an internal audit, a business can fine-tune and streamline its business processes, ultimately using performance metrics to improve its productivity and revenue.