How many DQ Reports is neccissary?

Question

Hi DQ team, one of my customers would like to get a better understanding of how many DQ reports a big international retail company of their size usually maintains (100, 1000, 10000). I know this is a very generic question, but maybe we have some best practice from other (retail) customers? Thanks!

ericgerstner · Answer

“That is a great question, but I would liken it to how many reports development runs in JIRA/ServiceNow, sales in their CRM, or even finance in excel. Our goal is to make reporting valuable and not force a specific number”2 – explain the reality of reporting

“The growth of tools like Tableau has taught us the value of custom reporting with ease – most organizations scale to this with role-based reporting from BI teams. Our goal with CDQ is first to provide you with basic reporting needs, but at a company of Aldi’s scale – we understand you may use tools like Tableau, and we will support those reporting dashboards. The question is not the number of reports, but what roles need to know about Data Quality.”

Some reading to help consider.

5 reasons why over-reporting can ruin your business. And what to do about it.

If you ask managers and employees on different levels many would agree that they spend too much of their time on reporting. This includes report preparation, generation, compilation, reading and presentation.

Reading time: 4 min read

How to overcome reporting challenges in your business

Learn how to overcome some of the most common reporting challenges. Consolidate all your ERP and business data so reports are dynamic and accurate.

Bottom line, if you want a number, I can give some math below, but I would say it’s worth considering what your reporting capabilities are – not how many reports. Even using the word report is a misnomer to the fact that a report could be 1-metric or 100.

Below then are use cases you can discuss – each one highlights why they care and what CDQ can support in way of their inherent reporting needs. Presumably all of these roles already have reports, DQ would be a metric.

Consider how many business functions, presumably the C-Suite roles. Leverage PMP scale to highlight the 4 layers (Executive Portfolio Program Project). Business Functions x 4 layers gives you the rough number of potential reporting types. The number then would based on the actual amount of functional teams.

Ie) If they have 3 business functions, Grocery Operations-COO, Data Governance-CDO, Technology-CIO – you could argue for 12 types or reporting given scale.

The total number of reports is then a matter of version vs. vision (12 types of reports segmented as they segment operations – regionally for example)

ie continued) Grocery Operations may only need 7 total reports as they only care about reducing operational search for shrinkage due to bad data quality (1 Executive 2 Portfolio for US and EMEA 4 Programs for Canada, US, Europe, and Emerging Markets). The CDO may have 41 versions of their 4 reporting types given a flat org with data broken up into 10 project teams.

Examples below of why those business functions care…

Your CDO may not want to know specific breaks but will definitely want to know DQ coverage – CDQ provides exportable metrics on DQ coverage.
Your CRO may not care about working data but only alerting to issues in the process of his sale’s department committing bad data - CDQ provides exportable alerts to DQ issues that they should care about.
Your Chief Privacy Officer may have a vested interest into PII and sensitive data – with CDQ’s sensitive data detection, we can provide insight to support compliance with GDPR and CCPA.
Your CFO may have seen the predications on scale with our automate DQ, perhaps that persona would want the report to show DQ Coverage under DQ vs. Manual coverage the year prior.
Your CIO wants to trust his technology, with CDQ making inroads to tools like ServiceNow, the CIO may want to see reporting on the frequency tech teams are spending focus “fixing bad data”
Your CAO wants to trust his/her insight into the data, asks for a report on the number of “validated” DQ issues – data that CDQ maintains.
Your COO cares about the bottom line – see manual vs automation investing in data governance and says what is this saving us. I know a top tier bank that reports the financial impact of bad data by quantifying the discovered issues against the cost to fix vs. the cost to prevent as they use CDQ for preventing bad data quality.

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