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Thursday, 14 July 2016 00:00

Data Prioritization

Written by  Henry Morley
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In our previous Data Stewardship post we discussed the core component of assigning and communicating data ownership and accountability. We also created a “Data Stewardship Checklist” that can provide structure to assist in creating and maintaining the missing link. Click here to get the checklist.

Now that the data ownership has been assigned (see previous blog post), you need to prioritize what will be worked on first – and why. It’s critical to define and communicate the relative business value of data and establish processes accordingly. Let’s dive in…

Define high-level data map in tiers

The first step is to define your high level data map in your critical business processes. Specifically, this should be done in logical sets of data (for example, demographic data, versus relationship data, versus transaction data), not at a data field level. Part of this data map should include setting business impact criteria with each process owner and establishing data tiers with simple “ABC” ranking. A good rule of thumb is to categorize the “ABC” ratings, where “A” is Business Critical, “B” is Business Impactful, and “C” is Nice to Have. After you’ve set individual process owner priorities, consolidate the individual process owner priorities into a single consolidated view to make sure there’s no gaps in ownership and priority. Review the overall list for gaps and overlaps, and get the list validated with the individual owners.

Establish appropriate processes to your prioritized data

A key success factor is aligning the appropriate processes based on the priorities of each level of data. As is taught in best practice inventory management, you hand count “A” level items often. “B” level items may do spot counts, and “C” level items you just replenish when you’re out of them. You typically manage the quality of tier “A” data with exception reporting and dashboards, which presents useable information to you instead of having to dig through multiple data sources. An example might be having a dashboard showing all sales pipeline activities where the expected close date is now past-due more than a week.

Tiers “B” and “C” will require less rigorous and frequent audit components. For instance, tier “B” data might just include routine review of the business impactful data into specific job roles and responsibilities. An example would be someone specifically assigned to look for duplicate information between systems on a monthly basis. Tier “C” might be similar but on a less-frequent basis, or could simply be a reactionary process once incorrect data is identified. Setting appropriate processes, timeframes, and owners based on the relative business impact of the information is critical. Line up appropriate cleansing and audit processes with the business impact of the information so you don’t just have a one size fits all process.

Tie data to your accountability to organization roles

Once the data tiers are set and prioritized, and the appropriate data management processes are established, now you want to tie them to the ownership and accountability in your organization. As described in the first post in this blog series, you’ve already established data ownership, now you need to include data process ownership to specific roles and people. To the extent you can, you should establish these new responsibilities in the Human Resource processes such as job descriptions and performance evaluations.

In the next blog post, we will discuss the specifics of how to build quality into the data management processes as part of overall data stewardship.

Want to see more detail on how to get started? Download the Data Stewardship Checklist, and sign up to get email updates from the Data Stewardship blog series where you’ll receive more information about organizing and maintaining your data assets. We’ll send you subsequent emails for each of the data stewardship areas outlined above.

 

Read 410 times Last modified on Thursday, 14 July 2016 14:39