Progressive Components (Procomps) is an independently operated developer and distributor of componentry and software for the production tooling industry. Progressive’s exclusive innovations are designed to speed mold builds, reduce costs, and minimize downtime. Their products are made with the highest of standards and are available through direct distribution and authorized dealers throughout the world.
The company wanted to see the actual sales performance of the current year and prediction of sales in the following year in one place to analyze the data. The reports would be utilized to guide account sales planning and inventory planning.
To achieve this goal, we chose Microsoft Dynamics 365 Customer Insight, Azure Data factory and Azure Machine Learning. This allowed us to combine all customer related data and provide a 360 degree view for the account and sales level executives.
The Progressive Component data is available on 2 different platforms i.e ERP and CRM in different formats. The challenge was to clean the data and provide a 360 view of the customer record that could be used by account and sales level executives. Further, they wanted to do sales activity palnning and inventory management utilizing current data to create predictions of future activity. Their wish was to see the current data and predictive data in one place, customized for the internal account and sales executives.
Customer Insights is an application within Dynamics 365 with pre-built connectors available. Using those built-in connectors, Cloud 9 connected the Dynamics & SQL data very seamlessly. We leveraged ADF for cleaning and data transformation. Then the data was used in Customer Insights for unification that provides the total number of customers and creates a 360 view of each customer.
Microsoft Azure Machine Learning Studio is where data science, predictive analytics, cloud resources, and your data meet to build, test, and deploy predictive analytic solutions on your data. We ingested the unified customer profiles and the sales measure into the Azure Machine Learning. We developed a time series Algorithum model that predicted sales for next year and created a pipeline to connect to Customer Insights. The models were published as web services that can easily be utilized by many Microsoft applications like Power BI, Excel, and Customer Insights.
The client is able to predict the future sales for a specific time and product to enable the team to manage inventory, estimate cash flow, increase customer lifetime value and provide a 360 view of the customer.