Onebridge recently worked with a leading manufacturer and supplier of components and related products for multiple industries, including HVACR, electrical, consumer hardware retail, electrical utility, automotive retail and the pool and spa channel. This client had data coming in from all over the world, with branches in the UK, Canada, South America, and more.
The client achieved a number of important milestones. Primarily, their teams no longer had to waste time manually creating financial reports. Now, data visualizations provide trustworthy and valuable insights to business users across departments, eliminating departmental silos and uniting the team around a single source of truth to drive impactful business decisions.
Sales demand forecasting has also improved, minimizing inventory levels and maximizing buying power. Budget forecasting has been completely automated and takes less time with better forecast accuracy, and sales resources can now be allocated where they are needed -- all because the business is now using their data as an asset thanks to a more mature business intelligence and data strategy.
The client’s forecasting and reporting processes were manual, taking several steps and days to complete. The sales cycle was correlated to the changes in seasons, but they didn’t fully understand the correlation or how to use it to their advantage. The relevant data was available, but the processes, technology and expertise needed to fully understand the best actions to take were not available.
The team’s data mart was also not performing well thanks to a lack of full systems integration and lack of clean data. Good quality data is the key component of any data driven decision making environment, which in turn leads to better business intelligence strategy modeling. There was also no standard process for new product launch information or analysis, making it difficult to gauge performance, find opportunities to improve sales and perform a thorough market research strategy.
As often happens with manual reporting and forecasting processes, mistakes proliferated and the insights found weren’t trustworthy, making it difficult to make confident and informed decisions. Without the ability to plan for changes in seasonal demand or reference historical data in sales forecasting, they couldn’t optimize the sales cycle or ensure success.
Inventory overproduction and misallocated sales resources added to the team’s challenges and led them to spend unnecessary money on related costs. They had no immediate insight into how the business or new products were performing, and couldn’t efficiently distribute reports--especially among the traveling sales teams who needed them most.
While the client was collecting a significant amount of data, manual processes made it impossible to properly govern the data or trust the insights gained from it. As a result, their teams were unable to get the immediate insights they needed to inform key business decisions.
With the correct platforms and processes now in place, their teams can make informed decisions based on immediate insights from trustworthy data. All business users are operating from one single source of truth, keeping teams in lockstep with one another as they work toward key business goals.
After spending time gathering Information to understand reporting requirements, needs, and current pain points, Onebridge constructed a framework and delivered a centralized agile business intelligence reporting system -- a complete makeover of their business intelligence strategy to enable more mature use of data. Now the teams have a centralized and consolidated dashboard for multiple reports, with interactive visual dashboards connected directly to a fully integrated data mart.
Onebridge also constructed a model in Tableau to improve their pricing strategy, and showed the client how to use weather data with predictive analytics to predict the seasonality of demand. They can now review historical data to see how much they sell at certain temperatures and what kind of correlation exists.
Their budget forecasting is now done based on modeling in R that completely automated the process into a monthly cadence. Every sales team now has an iPad with Tableau visualizations, with all teams accessing one central dashboard instead of each person maintaining their own spreadsheet. When demand is low in a certain region at a certain time, they are now able to predict that demand and allocate those sales resources as needed.
New Tableau dashboards showed valuable insights on industry benchmark KPI analysis resulted in a true picture of how the company is performing compared to other similar key competitors in the industry. With this new development, it is now much easier to conduct a strength and weakness situation analysis within various departments within the organization.