Our team undertook a consulting engagement with a utility company that wanted to improve its use of data in business decision-making. Before implementing new technologies to solve the problem, the company did something that many other organizations would do well to emulate: it conducted a data strategy assessment and established a data governance program.
We frequently encounter organizations that race to implement promising new technologies without (1) first determining whether these will truly be useful and (2) first establishing a data governance program that will lay ground rules regarding use of the technologies. We see precautionary steps analogous to these taken in society all the time. Traffic lights, stop signs, and speed limits are implemented before roads open to the public; similarly, we don't drive cars without seatbelts, brakes, and headlights.
Taking these pragmatic steps before an implementation takes place can keep potential problems from becoming actual problems, saving an organization time, money, and needless rework.
A data strategy assessment is a three-step process intended to help an organization understand where it is today, where it wants to go, and how to get there.
- Assess the current state. At the utility company, we interviewed key stakeholders - people who use data to drive decisions - to understand their current use of data and to uncover any issues and inefficiencies affecting their teams. Before moving to the next step, we presented our findings, confirming that the assessment was consistent with what the data users were experiencing.
- Paint the future state. Based on the assessment and on the company's business objectives, we proposed a data governance program as well as the implementation of a data warehouse overlain by a business intelligence tool.
- Develop a roadmap. We worked with the client to create a roadmap that would help the company move from the current state to the future state, with a prioritized list of specific initiatives.
One of the first items on the roadmap is the establishment of a comprehensive data governance program. Data governance deals with such questions as the origins, or lineage, of data; who can access data and what they can do with it; how to use metadata to catalog and organize data; and establishing guidelines for data quality.
Understanding who has access to data and how they are using it can help improve data security, enabling the company to restrict access to sensitive data such as customer names, addresses, and Social Security numbers, as well as competitive intelligence data used in business decision-making.
The data governance program's metadata component enables the utility company to catalog all organizational data and establish a single source of truth. Metadata helps the organization understand exactly what data it has, what each field in a dataset means, and how it should be used in analyses. That puts all data users on the same page and helps them avoid potentially messy problems; for example, applying conflicting business definitions to the same data. If one analyst calculates a business metric one way while another analyst derives it based on conflicting logic, business decision makers may receive divergent analyses on that topic. Properly managed metadata can prevent such problems.
The utility company's data governance program also establishes data quality standards. These will help the organization determine what is an acceptable level of quality and then flag errors arising in daily data feeds. That will help keep the data warehouse from becoming overwhelmed with unreliable data that can undermine decision-making.
In connection with the governance program, the company established a data governance council, data stewards, and data owners to drive data issue resolution and data innovation initiatives. As new sources of data are evaluated, there will be processes in place to help data stewards and data owners determine whether the data will be stored in the data warehouse; how the data will be cataloged with metadata; who will have access to it; and what quality checks will apply to it.
Conducting a data strategy assessment and developing a data governance program before implementing new technologies can help ensure that an organization selects the right technologies for its business needs and that users of organizational data can work with confidence and efficiency as they improve organizational business decision-making. Those are advantages that contribute directly to the bottom line.