“Data quality (DQ) programs are often not aligned with the strategic objectives of the organization. These misaligned programs fail to help business stakeholders achieve organizational outcomes, resulting in opportunity cost.” 

To enable a data-driven organization, data & analytics leaders must take pragmatic and targeted actions to improve their enterprise data quality.”

The first six actions focus on where to start and who is responsible:

• Action 1: Identify a Business Case - “Identify specific business outcomes that can be influenced by improving DQ.”

• Action 2: Define DQ with Stakeholders - “Get alignment from stakeholders on definition and expectation of DQ.”

• Action 3: Establish DQ Standards - “Establish DQ standards for critical and commonly-shared data elements across the enterprise.”

• Action 4: Include DQ to D&A Governance Initiatives - “Have a holistic view of data governance requirements across various business operations.”

• Action 5: Establish DQ responsibilities in the Data Steward Role - “Dedicate data stewards from business units and the central D&A team.”

• Action 6: Form DQ Special Interest Group - “Data quality is a team sport. Everyone plays a part.”

These actions should be used as the basis for action when business outcomes are impacted due to poor DQ. If organizations already have well-established practices, these actions can be used to benchmark current practices and address existing gaps.

“Analytics help create more impactful metrics by bolstering your organization's ability to measure, classify, and decide.” 

“To make metrics that matter, create positive outcomes by focusing on key areas of business value: resource allocation, conversation optimization and comparative benchmarking.”

Resource Allocation: “Analytics — in particular a precise system of measurement — enables organizations to allocate just enough headcount, budget or inventory to balance the cost/quality trade-off.”

Conversion Optimization: “Analytics — specifically the capability to classify with granularity — enables organizations to personalize their business processes and, therefore, improve conversion ratios.”

“True comparative benchmarking is difficult and requires a trusted data aggregator to collect data at a low level of grain and calculate the metrics consistently across all peers.” 

“Through comparative benchmarking, organizations can identify the positive outliers, learn their best practices and use them to remediate the negative outliers.”

“Social fractures occur when we disengage with each other, when we engage only in a polarized way, or when we act negatively towards the common good.”

“In total, there are 12 social fractures, and lack of trust is the most impactful social fracture.”

“In terms of what lies ahead for society and organizations that are part of society, social cohesion and the power of the voice of society are two critical uncertainties.” 

“If you combine these 2 dimensions, there are four scenarios on how society could turn: Get With the Program; Play to Your Purpose; Mind Your Own Business and Wait for It.”

Get with the Program is all about collaboration. “Data sharing between businesses that are all involved in social programs is the default. Be ready for environmental, social and governance (ESG). Invest in AI for Good and Data for Good.”

Play to Your Purpose: “The most important thing is to plan for data sovereignty. Be sure that you know your data is stored at the right location and invest in sentiment analysis and master all forms of customer segmentation and clustering.”

Mind Your Own Business is the place where D&A leaders can focus on data hoarding. “Collect as much as you can about your market, and scale. Invest in competitive intelligence and use AI for hyperautomation.”