How do I get the entire enterprise aligned on data management?
To deliver the promise of D&A initiatives, finance pros are stepping into a leading role on establishing quality data management foundations.
When everyone is responsible, no one is accountable. It’s a classic business conundrum that many companies are facing as they try to harness the power of data and analytics (D&A) to deliver truly impactful new insights.
The “Data Is Everyone’s Job” mandate from the C-suite is great for raising awareness companywide, but then someone needs to drive the underlying business goals and execution. Increasingly, the finance team is stepping up to play the influencing role, expanding its portfolio of services, partnering with other essential teams and generally ensuring that ongoing D&A initiatives are business-led and technology-enabled.
Yes, data is still everyone’s responsibility. But given their regular involvement with data across the company, the CFO, CAO and their teams—uniquely—can make sure that “everyone” isn’t doing that work in silos. Enterprise coordination is especially important for data governance and management—the critical operational component of successful D&A solutions.
Effective data management frameworks focus on more than short-term quality improvements or implementing technology to “fix” data issues. Changes are sustainably made through strong governance and standards, new ways of working and a data-first enterprise culture that is strongly influenced by finance.
The Big Data Picture
So, where is the newly commissioned finance team to begin? Start with a clear understanding of the overall enterprise data management (EDM) workflow, which includes seven data-specific functions: acquisition, distribution, governance and management, reporting, advanced insights, security, and support and operations.
While finance is not responsible for every area, it is uniquely qualified to coordinate the “business-led” focus across each data function, given its regular interaction with other key teams like customer and sales, supply chain, information technology, and legal and compliance.
With that overall data management framework in mind, the finance team can drill down further, adding and expanding its expertise in key areas that set the foundation and example for enterprise-wide data integrity, while also seeking continuous improvement to maintain alignment with business strategies
Here are six critical areas of data governance and management, and the finance team’s role as it adds these capabilities to its catalog of services going forward:
Stay tightly involved in the structure of data sets that influence financials and operational performance, and proactively develop and update the finance data model as the organization evolves.
2. Master data
Focus on key master data that aligns with strategic goals, and identify ongoing improvements to properly gauge performance insights.
Identify opportunities for increased consistency in the data landscape, and then communicate finance data model impacts, both downstream and upstream.
4. Data quality
Develop mechanisms for ensuring financial data integrity, and assess automation opportunities to validate data more rapidly.
Increase knowledge of core data technologies to become more self-sufficient, automated and generally ready to leverage technology advances to optimize data model processes.
Collaborate with other business functions to determine gaps in critical financial insights, including an analysis of any internal or external forces that necessitate data changes.
Chief Evangelist Officer
Of course, that well-planned data management workflow won’t mean much if other parts of the company are not on board or simply not aware of the evolving D&A best practices. Here again, finance can advance its own teams’ capabilities while evangelizing to the enterprise as a whole.
Our KPMG teams have seen a number of common traits in companies that successfully optimize the entire organization for D&A enablement—starting with finance in an influential and often leading role.
Enterprise-wide advocacy efforts like an analytics skills audit and setting up a centralized analytics center of excellence can help sharpen internal capabilities and refocus recruiting efforts. Also, consider a cross-functional data governance and management working group that defines the master data model and regularly reviews it for updates.
Other leading practices for enterprise D&A enablement at high-growth organizations:
- Acquiring the right talent.
- Training programs (internal and external) to improve D&A skills.
- Sharing D&A knowledge between users and groups.
- Actively publicizing high-value advanced analytics projects.
- Driving the use of advanced analytics across the entire organization through centralized D&A coordination and cross-functional collaboration.
- Defining clear roles and responsibilities across the organization to ensure that the D&A and overall corporate strategies are aligned.
What Success Looks Like
Well-designed data governance and management is essential for any company’s D&A hopes and dreams.
As an example, KPMG recently helped a $20 billion wholesale distributor overcome pervasive master data management challenges across suppliers, vendors, locations, products and its internal chart of accounts. Our experts collaborated with the client to revitalize the quality, consistency and operational use of the master data across multiple disparate systems into a singular, consistent data source.
The client’s Enterprise Data Organization was established to promote new ways of working, while optimizing talent to interact with the business in a more strategic manner. By transforming the data model, KPMG helped the client establish a future-focused, scalable and effective foundation for their ever-changing business landscape.
Getting data governance and management right might feel like “the details,” but it’s critical to delivering successful D&A outcomes. And while everyone in the company may be engaged, it is finance that is truly invested.