Lately, the things we eat have come under increased scrutiny. We have been surprised at the places where tainted ingredients show up and the extent of their harmful effects. We want our food to be delivered efficiently and its ingredients to be healthy for long-term prosperity. The value of locally grown produce, with fewer transactions in the supply chain, is being understood more fully. This helps us ensure reliable sources and easier delivery methods, avoiding extra processing and contamination along the way.

Transit authorities have begun to apply the same level of investigation and continuous improvement philosophy to key operational data. It turns out that a relatively few elements of critical data shape many of our real-time decisions as well as our periodic reports and planning. You need these data elements to be timely, accurate, consistent across reporting periods, and obtainable without a lot of labor-intensive effort.

It is not just an academic issue. All of us have experienced firsthand the side effects of consuming unhealthy data.

Generally in the information technology (IT) industry, poor data quality can add 10-20 percent to operational budgets, with even higher rates in the service sector. Just imagine if your operational costs were 20 percent lower or, better yet, you could deliver 20 percent more service, largely based on existing assets and communications/IT infrastructure.

So, we thought it would be fun to share with Passenger Transport readers a sample questionnaire, highlighting some of the most important data elements and best practices identified in our Transit Data Fusion program. This questionnaire has no right or wrong answers, just a brief discussion after each question.

We encourage all transit professionals to go out and find the answers in their organizations; if nothing else, you will spend some quality time with people in other departments and generate some good discussions. You may be dissatisfied with some of the answers you find, or you may have trouble finding a good answer, and hopefully that will spur you into action.

The Questions
1. How many devices must a rail or bus operator log onto before entering revenue service or starting a new trip? How much pre-trip time is associated with device boot-up and logon?

With the proliferation of on-board devices, single-point vehicle logon is becoming increasingly important. But it is easier said than done; to do it right requires both on-board and back-end integration of several systems, as well as data pre-load before pull-out. If the bound record of operator ID, train/bus ID, and work assignment is captured correctly on every trip, and immediately made available to other systems, there are huge benefits. It turns out that this bound record is key to much of the operational data quality discussed throughout this questionnaire.

2. Are your dispatchers able automatically to get health reports and critical alarms from trains and buses that are in service? If so, can they dispatch replacement service before a vehicle fault causes a service disruption?

In a few cases we have found transit authorities that have adopted a “zero disruption time” policy, through the deployment of “strategic” replacement trains and buses. Traditionally this required an onerous commitment of standby rolling stock. But given today’s technology, it is possible to take a flexible, data-based approach to on-road service quality while maintaining an acceptable vehicle and operator spare ratio.

3. Are you confident enough in your on-time performance and missed trip data that you regularly sit down with your operators’ union representatives and jointly discuss ways to improve? Do you make OTP and trip reports available to your customers?

With the right amount of system integration, it is possible to drill down into aggregate OTP and trip numbers and pinpoint specific problems. It may be that a few particular trips or just a couple of operators are skewing the data for everyone.

4. What is your lag time between collecting fare collection and passenger count data and making service adjustments as a result? Do you track vehicle load factors on each route and trip?

For many transit authorities, the lag time can be six months or more, with no clear feedback process into trip planning and scheduling. However, some do it as often as weekly, and have negotiated flexible work rules to support this level of customer responsiveness and efficiency.

5. Is your vehicle mileage data estimated or actually measured? Is it collected automatically from a single master source? Are you able to accurately separate revenue and non-revenue vehicle miles? Do you encounter large variations in mileage from one reporting period to the next?

Vehicle mileage is one of the most important data elements and has ripple effects throughout the organization. It drives everything from scheduled maintenance to funding and reimbursement. With current technology and some system integration, it is possible to achieve good accuracy and reap many benefits.

6. What percentage of your line maintenance employees are users on your central maintenance management system? Do they use it 100 percent of the time for work order data entry, electronic service manuals, and parts picking?

Given the state of some maintenance management systems, considerable data on maintenance events may never be captured. People develop lots of shortcuts and work-arounds because of system limitations. Often this happens not because of inadequate software functions, but instead due to poor quality reference data, poor availability of data terminals close to where the maintenance work is actually performed, and other aspects of the system affecting user friendliness. To help bridge this gap, handheld wireless devices for maintenance and other yard/shop functions are becoming more feasible.

7. From their PCs, do all members of your management team have direct access to reports and querying capabilities in all major operational systems? Is it available from a single integrated source?

In some cases we have counted a dozen or more transportation-related systems in a single authority, with overlapping and sometimes conflicting data. There is a big need for standardized data warehouses and business intelligence systems to broker the timely, accurate, and complete interchange of data between legacy operational systems and allow them to remain unchanged when new “casual” users are added.

8. Have you ever assessed the benefits of improved data quality in terms of cost savings, improved customer service, increased revenue, improved safety, and funding/reimbursement advantages?

So, how did you and your organization do? What did you learn and what areas of improvement are you most interested in? We encourage you to pursue projects around the highest-priority items you discovered. Maybe you can’t say your data is “certified organic,” but we could all benefit from a healthier, more cost-effective transit management lifestyle based on the highest-quality data ingredients.

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