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Rocky Mountaineer

Karen Beckmann, Senior Director, Information Technology

Running a Robust Data Management Plan

Karen Beckmann

Since delivering tangible business value is paramount to business success, this becomes an important IT challenge. The challenge is to show business value in data management, which can be so theoretical and academic.

Big Data Challenges

Let us begin by examining predicaments faced by IT teams when trying to deliver value.

First, poor data is the biggest challenge to the IT industry today.

Second, there is a latent need regarding report management and data output. Businesses tend to have more reports than governing capacity, so administering those along with the data is an important issue to tackle.

Finally, third-party data sharing can be difficult, but partners must manage data together, so business opportunities are not lost.

Transforming Data in the Rocky Mountaineer Way

As a luxury train operator offering journeys that showcase the most spectacular scenery North America has to offer, Rocky Mountaineer's most important focus is on the guest experience. We have strong and evolving analytics in this space – and we rely on that data. We are also pursuing new metrics of success such as effective ticket price, train utilization, capacity, and channel distribution. To be successful with a new data endeavor like this, I recommend finding data advocates. Rocky Mountaineer's dedication to data value is demonstrated with a commitment to data-driven strategies by every member of the senior leadership team.

Rocky Mountaineer also addresses data challenges by deconstructing siloed analytics, data, and IT functions so they can work together. With a “one-team” approach, gaining support and funding for data resources and activities should be easier. This approach assists in identifying a critical data focus.

Once you have data advocates and a critical data focus, you will be ready to start managing data and delivering tangible business value.

Managing Data:How to Start

It's best to begin by identifying the most important data consumed by the company. Most IT teams might gravitate towards big data or invent innovative analytics. My advice is to take time to interview business leaders to understand the most important reports and shine a light on them.

I take that approach when prioritizing data at Rocky Mountaineer, and follow these process steps for data governance:

1. Once you have your critical data focus, identify and agree to the report list in the Critical Report Catalog.

2. Understand data fields supplying critical reports, then prioritize those data fields.

3. Extract, agree, and publish formulas and business rules that have been built into reports; capture this in your business glossary.

4. For critical data fields, identify source systems and accompanying changes (data lineage), and capture all of these in your data catalog.

5. Work with your data advocate and data owner (preferably who creates the data) to define data quality standards.

6. Profile that data against standards to understand where corrections are required.

Data management is not just about cleaning up data, but about changing the culture of your company. Your data consumers will indicate the impact clean data has on their confidence and trust.

7. Work with source system owners (IT and business) to understand if source systems configuration (drop-down values and/or mandatory fields) and business processes can be changed to produce data to quality standards.

8. Run a script to complete a one-time data correction (ensure that you conduct a regressiontest of the impact of this data change before you move to production).

9. Run the clean-up script regularly until source controls are achieved and educate users on why they may temporarily see different results in the source versus your reports.

10. Publish quality reports through data profiles regularly (monthly) for the data owner and ensure they are incentivized to maintain quality.

Always remember the importance of delivering tangible business value. Do this through a robust change management and communications plan. Data management is not just about cleaning up data, but about changing the culture of your company. Your data consumers will indicate the impact clean data has on their confidence and trust. In addition, create a report and data certification process that gives others their confidence and trust in data. Articulating which gold-standard, trustworthy empowers data use.

Once your culture is changed and data is clean, you will discover what the industry means when they say, “data is the new oil”.

The articles from these contributors are based on their personal expertise and viewpoints, and do not necessarily reflect the opinions of their employers or affiliated organizations.