The application of artificial intelligence (AI) to data analytics continues to be a growing area of automation technology. In analytics applications of AI, the AI technology typically remains comfortably behind the scenes and out of reach of the user. As such, the AI is like the old Intel Inside ads launched in the 1990s in that it powers the system but you don’t interact with it directly as a user.
New advances in technology surrounding AI are making this complex area of computing more understandable and interactive. An example of this interactive AI can be found in Conversight.ai’s Athena smart assistant.
“Users of Conversight.ai’s supply chain optimization software can ask questions such as: What are shipped revenues for this year? What is our revenue by inventory order? or What are our top products by SKU?” said Howard. Questions can be asked via voice or text.
The data to provide these answers are pulled from enterprise systems as well as customer-facing online and social systems. Howard said the company has more than 100 built-in drivers to enterprise systems such as SAP and e-commerce systems, as well as Google Analytics and basic data collection software such as Excel.
Howard said interaction with the system starts with your “need to know” insights provided by Athena that offer a big picture overview of your supply chain operations and where issues might occur. Based on questions users ask of Athena, in addition to the system’s regular reports, Athena then analyzes the trends “so you don’t have to keep asking those questions,” added Howard.
According to Conversight.ai, personalized analytics delivered via interaction with the Athena smart assistant—rather than standardized analytics reports—enables the reports to address specific user preferences, parameters, and metrics. It also helps filter out unwanted data for more organized dashboards to focus user attention on what they need and want to see.
Workbenches in the Conversight.ai platform address automation of demand planning, supply planning, and production planning. “It also monitors forecasts by actuals to help users see where they need to pivot,” said Howard. “The software also helps assess the business impact of stockouts and learns how to place orders based on lead times to avoid future stockout situations.”
Common issues addressed by the Conversight.ai’s platform include:
- Monitoring safety stocks since, with today’s supply chain disruptions, users can’t “set and forget it anymore,” Howard said;
- Forecasting stockouts through more accurate demand projections;
- Automating creation of new reports, dashboards, and purchase orders;
- Identifying non-moving inventory and segmenting products, vendor, and customer data to better understand supply chain movement; and
- Receiving alerts for price increases so that manufacturers can add costs to quoted prices before margins are lost.
During his presentation, Howard discussed the use of Conversight.ai’s platform by MavPak, a packaging materials and distribution company. “We started working with them in 2018 when they had $3 million in revenues and seven employees, two of which were customer success team members. After setting up the Conversight.ai system to create a self-service environment for employees, automating purchase order generation, and producing business insights, MavPak has experience 7x growth, with hundreds of new customers, and has only needed to add one new customer success team member to handle this growth.
Read this story about how AI technology is increasingly able to explain itself.
Leaders relevant to this article: