Manufacturing & Industrial Engineering
North America
Managed Analytics
Inefficient Workflow:
Outdated systems and manual processes slowed the automotive manufacturing line. Without real-time insights, delays and inefficiencies became commonplace. The need for a streamlined and modernized workflow was clear to boost overall efficiency.
Supply Chain Bottlenecks:
The automotive company struggled to spot and tackle supply chain bottlenecks. This led to frequent stockouts and overstock situations, impacting profits. Streamlining the supply chain became crucial to respond promptly to market needs and ensure sustained profitability.
Data Silos:
Data scattered across various systems created a headache for the automotive manufacturer. Without a central hub, gaining actionable insights became cumbersome. Integrating data for a unified view was essential to enhance decision-making and overall operational effectiveness.
With the discussed challenges, our data engineers implemented end-to-end tailored analytics for manufacturing optimization in place:
Custom Power BI Dashboard: Curated a customized and user-friendly dashboard designed to offer real-time insights into Overall Equipment Effectiveness (OEE) scores and comprehensive manufacturing performance, empowering the stakeholders (deployed developers and internal team) with a deeper understanding of operational efficiency and productivity.
Data Warehousing: Consolidated data into a centralized warehouse, enabling seamless integration for a comprehensive view of operations in the automotive manufacturing sector.
Our deployed data engineers ensured that the implemented solutions(managed analytics framework and the custom PI dashboards) are practical and real-time, hence it yielded these positive outcomes for the automotive company:
Improved Production Efficiency: Reduced production delays by 18%, ensuring a smoother workflow.
Increased production output by 15%, meeting market demands with enhanced efficiency.
Supply Chain OptimizationCut stockouts by 19%, addressing supply chain bottlenecks.
Boosted overall supply chain efficiency by 12% through improved inventory turnover.
Stakeholder Communication:Facilitated transparent communication with stakeholders, ensuring alignment with immediate operational objectives.
Improved OEE Score:Provided real-time insights on the supply chain through a custom dashboard, enabling quick decision-making.
Improved Overall Equipment Effectiveness (OEE) score by 12%, optimizing production machinery and reducing downtime.
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DataToBiz is a good choice for someone who wants a partner who understands the product journey, requirements, and delivery expectations. They have the experience and agility to understand what’s possible and deliver to the client’s expectations. They‘re really passionate people, and they know what they’re doing!
We’re impressed with DataToBiz’s professionalism, dedicated support, and consistent follow-ups. Their team maintains clear communication through online meetings, ensuring a smooth and reliable collaboration.
A solution like this is a good fit if your teams spend more time collecting and reconciling data than acting on it, if reports from different departments do not match, or if decisions depend on delayed or manual reporting. It also fits when your data is growing in volume or sources, and your current setup struggles to keep up.
DataToBiz starts with a discovery call to review your goals, data sources, and reporting gaps. You get a clear view of the expected outcomes, effort, and timeline before any commitment.
Yes. Every solution DataToBiz delivers is configured around your industry, business processes, and existing data environment. The team assesses your current systems, data quality, and reporting needs first, then designs a solution that works with what you already have instead of replacing it. This applies across industries such as manufacturing, retail, healthcare, finance, and logistics, and across setups ranging from legacy databases to cloud data platforms.
DataToBiz works across the major analytics, cloud, and data engineering stacks. For BI and visualization, this includes Power BI, Tableau, and Looker. For cloud platforms, it includes Microsoft Azure, AWS, and Google Cloud. For data warehousing and processing, it includes Snowflake, Databricks, and SQL-based databases. Data sources include ERP and CRM systems, spreadsheets, APIs, IoT and sensor data, and third-party applications.
If your stack includes a tool not listed here, the team can assess compatibility during discovery.
Most projects with DataToBiz take from a few weeks to a few months. The timeline depends on how ready your data infrastructure is for the initiative and how many systems need to connect. Smaller solutions go live quickly, while larger programs roll out in phases so you see value early. After an initial discovery call, you receive a timeline with clear milestones.
Security and governance is part of the plan from the first conversation. DataToBiz works within your security policies and follows the regulations that apply to your industry. The project usually Access stays limited to the people who need it, and confidentiality terms cover the engagement from kickoff to handover.
The work does not stop at go-live. Your team gets a proper handover and guidance on using the solution, and DataToBiz stays available for questions and improvements. The business impact of the project is measured against the goals set at the start, so you can see exactly what changed for your company.
