Championing the Data (A collaborative approach)

Championing the Data  (A collaborative approach)

When we hear champions of data, one person such as the CDO (Chief Data Officer)  comes to mind. Having one person who will and who should champion organizational data has challenges.

Some of the challenges with this approach are:

  • Lack of buy-in from across the business teams
  • One person leading could result in burnout
  • Will not have varied/different perspectives on data challenges
  • Gives the wrong perspective that data championing is one person’s responsibility

An alternative and better approach is to set up a champion team. A winning team has many players playing specific roles and responsibilities. CDO can help the initiative in the support role by driving from behind. CDO can lead hands-on in technology implementation. Such a model would have a long-lasting impact.

Let's examine classic why, what, who, how, and when aspects of this collaborative and shared approach to data championship.

Why

Knowing and well-defined “WHY” can help galvanize the support across the organization. It should be business-driven to gain momentum and support across the organization.

A recent Accenture study reported that only 32% of organizations are able to realize tangible & measurable value from data. Close to 70% of them are not able to unlock the hidden value.

Collaborative team helps identify business opportunities. It also develops a better data-driven culture.

A joint ownership brings different perspectives. It helps focus on items that give better ROI and bring in more resources to help.

What

The biggest pain point or greatest business opportunity can drive the scope. Defining a specific measurable and deliverable scope helps the chances of success.

The initial project can be very specific such as:

  • Reducing the plethora of excel spreadsheets juggled by the finance team.
  • Building consistent data labels, data formats across reports for the customers
  • Building a centralized and well-defined data catalog
  • Building centralized data quality checks to improve data onboarding operations
  • Identifying specific value adds for each department (depicted below) would also help.

Who

Everyone with a stake and interest in data can take part and contribute.  This can be from inside and outside the organization. Some of the contributors can be:

  • Business executives from finance, operations, sales, customer success
  • IT executives such as CTO, CSO, CDO
  • Data enthusiasts across the organization
  • Customers
  • Vendors/partners

Here is an example of the matrix structure of this group. Each organization can also define the specific definitions of these roles by the department. As an example, Governance oversight for finance may lean towards audit, and access management while for IT/CSO it may lean more towards data security and compliance.

How

How to start: The best way to start is to take up a smaller segment that has pressing business needs.

How to sustain: Sustaining is critical as this is more of a marathon than a sprint.  Here are some tips that would help keep the engagement sustained.

  • Celebrate the wins
  • Take an iterative approach vs a big-bang approach
  • Rotate team members for an opportunity to take part and experience the ownership

How can technology help: Modern data technologies can help speed up the process. These technologies should include automated data lineage, data cataloging, and data quality. Many of these tools have features to bring in business teams to collaborate with IT.

How to measure success: Measuring success helps celebrate wins. It can bring a snowball effect in participation and enthusiasm across the organization. Here are some KPI metrics to consider:

  • Increase in revenue
  • Reduced costs (less rework, faster data ingestion …)
  • Reduced risk (such as faster and higher compliance with audits, fewer compliance incidents)
  • Improved brand awareness 
  • Increase in customer satisfaction levels 
  • Decrease in number of customer support tickets related to data issues
  • Speed & Accuracy of your data onboarding processes
  • Faster turnaround time in building a business insight/BI (Business Intelligence)  dashboard
  • Use Engineering DORA metrics for your data initiatives.
    • One point to note is that DORA metrics are developed with application engineering in mind. Principles of these rules such as adopting mean time to recovery (MTTR)  can be adopted to measure how efficiency we run data onboarding processes.

When

There is no wrong time to start. Certain events (such as customer pain reaching a boiling point) can bring the urgency to start.

Another good starting point is a few months before budgeting season.  This helps to bake-in budgetary requests for people and technology support.

Summary

In summary, there is a lot of potential in unlocking your data and it needs data champions across the board. Some of the actionable steps to consider are:

  • Collaborate with business leaders
  • Understand and define the “WHY”
  • Pick a business pain point/ opportunity to address.
  • Identify KPI metrics to measure the success
  • Bring in the right technology
  • Celebrate wins
  • Rinse and repeat.

Hope this provides a good framework to start championing your data. Data is like a small plant, it needs nurturing so it can grow and bear fruit.

 About the Author:

Jwala Vedantam has 25 years of experience in IT. He has 12 years of experience with data management, strategy, and architecture. He worked with Healthcare & FinTech Industries.  He specializes in stabilizing, standardizing, and scaling data management practices. He focuses on empowering analytics and data science teams with quality, timely and reliable data.

He lives in the Dallas-Fortworth metroplex. He enjoys practicing meditation and watching movies with his family.

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