About the Client
Known for its quality and reliability, the client specializes in crafting innovative, technologically advanced lighting solutions for the automotive industry. Their product portfolio includes a wide range of headlamps, rear lamps, and other lighting components, all designed to enhance vehicle safety, aesthetics, and performance. By combining cutting-edge engineering with stringent quality standards, our client remains a trusted partner for leading automotive manufacturers across North America.
Goals & Challenges
The company’s leadership sought to modernize outdated processes and systems, streamline operations, improve visibility into business performance, and identify opportunities to reduce costs where possible.
Achieving their goal required a carefully planned and phased approach, with each stage delivering measurable returns to justify further investment.
They also understood that implementing new tools and workflows would require a robust change-management strategy to ensure user adoption and minimize disruptions to the business. Driving end-user acceptance would be key to making the transformation stick.
Their digital landscape posed several interconnected challenges, each requiring thoughtful attention.
Fragmented / Siloed Data
Client’s critical business data resided across multiple disparate systems (Plex ERP, Kronos time and attendance, adaptive budgeting, and various HR applications). Without a unified repository, pulling data together was a logistical challenge. Creating a single management report could take up to 36 hours of manual Excel consolidation, delaying critical decision-making at moments where agility mattered most. In addition, their central SQL Server, which handled integrations, became a bottleneck, straining infrastructure and causing frequent service disruptions.
Operational Inefficiencies
Every day, client’s staff faced the tedious task of processing around 200 vendor invoices manually. Each one took 5-10 minutes to extract data, validate line items, and post into the Plex ERP system. This sheer volume consumed hours of valuable staff time daily. Adding to the complexity, invoices arrived in various formats (PDFs, scans, and email attachments), which made consistent data capture difficult and increased exception rates.
Solution
Bridgenext partnered with the client in a phased approach, combining strategy, data, automation, and interim support to tackle both the client’s long-term strategic goals and short-term pain points.
Phase 1: Data Realization Assessment & Roadmap
Over two weeks, Bridgenext conducted an in-depth assessment to map data flows across finance, purchasing, production, and HR, uncovering unseen connections and opportunities for improvement.
- Identified where manual handoffs and integration gaps slowed down processes, documenting opportunities for both smarter system integrations and process automation.
- With these insights, Bridgenext developed a future-state process model and a detailed change-management plan for smooth rollout and effective user training.
- A detailed business case was created with measurable KPI targets (e.g. invoice processing time, reporting cycle time), giving stakeholders the confidence to invest and see the ROI potential.
Phase 2: RPA-Enabled Invoice Automation
- Transformed manual invoice processing by building end-to-end invoice bots using Microsoft Power Automate (cloud and desktop flows). The bots extract key invoice fields, validate data, and seamlessly post entries into Plex ERP, saving hours of tedious work.
- Tackled unstructured invoice formats using Azure Document AI and Azure OpenAI, enabling intelligent classification of invoices as MRO or non-MRO, and ensuring business rules are accurately applied.
- Delivered impressive results: a 98% automation success rate for MRO invoices and 100% on non-MRO, virtually eliminating exception handling and streamlining operations.
- Replaced time-consuming manual reporting with automated Excel summaries, setting the stage for interactive Power BI dashboards that deliver actionable insights at a glance.
Phase 3: Data Fabric Pilot for Analytics
- Deployed Microsoft Fabric as a unified lakehouse to streamline data integration. We consolidated data from Plex (via SQL Server), Kronos (via BigQuery), adaptive budgeting, and HR systems through secure APIs, creating a single source of truth.
- Designed and built robust Fabric data pipelines and custom Azure Function apps, transforming raw data into actionable insights, while tailoring outputs to meet users’ preferred formats.
- Transformed labor and downtime reporting by automating the process, cutting down the previous 36-hour report cycle to near real-time updates, with data refreshes occurring 6–8 times daily.
- Introduced interactive Power BI dashboards for real-time insights, empowering managers with instant access to critical data and enabling more informed, on-the-spot decision-making.
Ongoing Purchasing Analyst Support
- Provided Bridgenext data analysts in client’s purchasing team to manage routine tasks, enable seamless knowledge transfer, and ensure business continuity throughout the transformation process.
Key Technologies Utilized
- Microsoft Power Platform: Power Automate (cloud & desktop flows), Microsoft Dataverse for workflow orchestration and data storage
- Azure AI Services: Azure Document AI & Azure OpenAI for intelligent document extraction; Azure Function Apps for custom data transformations
- Microsoft Fabric: Data pipelines, notebooks, and lakehouse storage for consolidated analytics
- Data Integration & Reporting: SQL Server, SSIS, SSRS, Microsoft Access, and Power BI for automated reporting and interactive dashboards
Benefits
- Cost Savings & Increased Productivity: By automating manual invoice processing, the client was able to reassign two full-time employees to higher-value roles, significantly accelerating the return on investment for their automation initiative.
- Real-Time Decision-Making: Clunky Excel reports were replaced with automated, near-real-time dashboards, empowering management with faster, data-driven decision-making capabilities.
- Improved System Stability: Mitigating integrations away from the central SQL Server improved system uptime and reduced emergency IT interventions.
- Higher User Adoption & Satisfaction: A structured change management strategy, coupled with embedded support, ensured a smooth transition. This led to higher user satisfaction and executive confidence in solution investments.
Results
| Metric | Before | After |
|---|---|---|
| Invoice Processing Time | 5–10 minutes per invoice | 2–3 minutes per invoice (50–75% ↓) |
| Invoice Automation Accuracy | Manual, error-prone | 98% (MRO), 100% (non-MRO) |
| FTE Allocation | 2 FTEs dedicated to invoices | Redeployed to strategic initiatives |
| Reporting Cycle Time | 36 hours per report | 0 manual hours (auto-generated) |
| Data Refresh Frequency | Weekly or slower | 6–8 times daily |
| System Downtime & Bottlenecks | Frequent service disruptions | Significantly reduced |
| Stakeholder ROI Visibility | Limited | Documented within 12 months |
Building on these successes, the client plans to expand the data fabric initiative enterprise-wide while also exploring predictive AI pilots for forecasting and maintenance.
