What Gets Measured Gets Managed: Improving The Quality of Data Feeding Supply Chain Metrics
To enhance your supply chain, measuring what matters is crucial. Focusing on specific Key Performance Indicators (KPIs) can drive improvements in transportation, costs, and sustainability. For transportation service metrics, measure on-time delivery and lead time variability. To improve transportation cost metrics, track capacity utilization and overall costs. Monitoring carbon emissions is essential for sustainability. Establishing a baseline for these KPIs and using a data-driven process to manage them can significantly enhance performance over time.
Different types of information feed into KPIs: descriptive, diagnostic, predictive, and prescriptive. Understanding these distinctions is key to effective data analysis and decision-making processes:
To simplify:
An example of these information types in action is Google Maps. Descriptive information gives you details about the route, current traffic conditions, and tolls. Diagnostic information provides reasons for increased traffic, such as an accident. Predictive information estimates your time of arrival, considering the factors in play. Prescriptive information suggests alternative routes and their tradeoffs.
In supply chain management, data is often fragmented across multiple entities and systems, making it challenging to consolidate the data required to measure performance. Suppliers vary in their data maturity, from basic spreadsheets to advanced automated systems. To derive necessary insights, you need to:
Measuring and managing data quality is fundamental to creating high-quality KPIs. Unity measures data quality across five attributes:
Unity's flexible data sourcing capabilities allow it to collect data via emails, flat files, manual uploads, and APIs, adapting to the maturity level of each supply chain partner.
In-app reporting identifies the source of data used for key attributes, enhancing user confidence. For instance, you can hover over any attribute in the system to see if it came from a specific supplier, carrier, or was calculated by Unity.
Unity’s data quality dashboards quickly identify the completeness and latency of key data points, crucial for making timely and informed decisions. For example, if you need to stay on top of origin operations for containerized shipments, you must track several data points. These include booking information with planned vessels and sailing schedules, terminal information about ERDs and cutoff dates, and container milestone information confirming moves from empty release through gate-in and all the way to loaded on vessel at origin. Measuring the completeness and latency of these data points ensures you have all the necessary information on time to make critical decisions.
Additionally, Unity provides time-phased prediction accuracy reporting to help track variability and make necessary adjustments. Measuring the accuracy of predictive insights, such as carrier ETAs and ETDs, is critical in helping track variability and make necessary adjustments.
Furthermore, Unity reports on the quality of data ingested from customers, including key identifiers such as container numbers and bookings, and reports on the reason for any failures. This enables collaboration with customers to accelerate root cause analysis for failures and drive continuous improvement.
By focusing on these strategies and utilizing Unity's robust data management capabilities, you can significantly enhance your supply chain's performance and achieve better business outcomes.
