A manufacturing client stored customer purchase orders and customer contracts on a cloud-based file repository. Outstanding orders were tracked in a spreadsheet, which was manual and tedious to keep up-to-date. As a result, management rarely had a real-time quantification of order backlog and could not assess monthly or quarterly trends with any consistency.
Approach
We implemented a major change in the pre-production process that enabled an accurate, real-time view of order backlog. This required all purchase order information to be inputted into the ERP system and linked to specific jobs in the production workflow. We then created queries to automatically pull the required data from the ERP system into a dashboard that allowed management to quantify all orders that were still pending at various stages in production.
Backlog visibility data could also be segmented in different ways, such as by production facility, by end market, by end customer, or by major product category.
Results
Real-time Visibility
- Management gained greater confidence in the accuracy and consistency of the backlog.
- Improved assessment of business trends on a weekly and monthly basis.
Earlier Corrective Actions
- The company identified underperforming business units and facilities earlier than could be achieved by analyzing revenue performance alone.
- Corrective actions could be made sooner to get the business back on track.
Conclusion
Order backlog can be an important leading indicator of performance in your business. It informs the annual budgeting process, helps with production planning and directs your sales efforts towards consumption of future underutilized production capacity.
In a company sale process, buyers pay for future performance and backlog data is often requested during diligence to validate near-term forecast assumptions. It is necessary to both quantify your backlog and show a history of consistency and growth.
If you lack visibility of your backlog, contact us to learn how to properly setup the required data capture and analysis.