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Your Missing Enterprise DNA

The ability to compare and contrast data-sets—the context of data—is key to achieving results from investments into business intelligence projects. One major hurdle organizations face is that much of the organizational ‘metadata’ they need to leverage their data assets remains in ‘analog’ format (such as paper documents) or is scattered across systems.

I frequently describe this metadata in articles and books as an Organization’s ‘digital DNA’. It includes the following data-sets:

  • Locations—The places where the organization operates from.
  • Organizations—The company structures in law (such as groups, companies, sales organizations, branches, affiliates etc.)
  • Organizational Units— The hierarchical structures that define where roles exist such as companies, divisions, business units, departments, teams, work groups etc.
  • People, Roles and Portfolios—Details of the people that work for (or on behalf of) the organization, the roles they discharge and the portfolios they are responsible for.

Note that it’s important to differentiate between people and roles given that people tend to be more transitory than roles. This is why most policy documents reference roles and not the names of individuals.

  • Systems and Data—What systems exist and what data they hold.
  • Capabilities and Processes—Describing the core capabilities of the enterprise (i.e. what it does) and the processes that are used to fulfill them (i.e. how it’s done)
  • Suppliers—The suppliers of the enterprise.
  • Sales Territories—The places where the enterprise does business.
  • Disciplines—The ‘things it does’ (normally the product lines and portfolios of the business.

It’s extremely rare for enterprises to possess all of this information and the data linkages between them in a single system and yet it’s essential to compare and contrast operational data through the lens of this metadata ecosystem.

To example this, if a sales executive is reviewing sales performance, they might reasonably want to know which teams are delivering the best results, the sales territory that is doing the best (so they can find out how and seek to replicate that success), the processes that are resulting in the majority of the cost of sale etc. Without this metadata to frame the landscape of insights, many of the questions executives want to be answered remain on the ‘no can do’ list.

How to Create your Organizational DNA

Most organizations already hold the missing data they need to make sense of operational data and to make their data culture happen. The challenge is that these data resources are fragmented and exist in pockets of IT and operational silos across the enterprise. The best way to resolve this problem is to create a new data warehouse that harvests all of your enterprise DNA and structures it in a way that makes sure its integrity can be maintained, and that it can be use and re-used every day.

Obstacles to Adoption

Common obstacles to adoption of a federated organizational DNA data mart include:

  • No reliable mechanism is thought to exist that can be employed to identify sources of data and harvest useful content
  • No data engine exists to organize and manage data
  • Concerns exist over data governance and threats to data loss when data is exported from systems brought together in a single place
  • It’s not known what data exists, or where it is
  • Data quality issues compromize the delivery or RoI of projects
  • No data relationships exist between important data sources (such as financial records, service records, transaction history records etc.) because the enterprise operates fragmented IT systems that create silos of data.