10 Tips From State Department’s Enterprise Data Strategy

Data transformation isn’t just a buzzword in the private sector. Earlier this fall, the U.S. State Department released its first-ever enterprise data strategy, which it called “a milestone in the Department’s transformation into a more data-centric organization.”  

Sound familiar? Organizations across sectors have focused on digital transformation initiatives, many of which aim to derive value and insight from data. The State Department’s strategy has a lot to offer, thanks to its clear focus on ROI and responsible data handling. 

Here are 10 of the strategy’s considerations for data collection, storage and use -- and how these considerations can inform digital transformation efforts more generally.

1. Data-driven Insights

The State Department’s strategy emphasizes high-quality data analytics capabilities. In addition to supplying employees with evidence-based information to act on, these capabilities aim to ensure operations run as efficiently as possible.

Tools like knowledge discovery frameworks are part of establishing successful data analytics capabilities. However, real transformation goes beyond just building the architecture. It’s also important for organizations to plan for growth and future data management needs. 

2. Keep Up With Innovation

The State Department’s strategy values technological innovation. The strategy focuses on equipping staff and partners with the best tech possible, because the U.S. knows other nations are doing the same. 

Similarly, enterprises must ensure they don’t lose ground on innovation. Doing so could create a reliance on dated technology and barriers to emerging technology. Organizations across sectors view digital transformation as a competitive advantage, so it's a risk for a company to lag behind.

3. Global View

The State Department must look far beyond U.S. borders. It needs to see potential foreign threats, of course, but it also must use technology to work effectively with staff and partners around the globe.

Organizations must consider how their enterprise data strategies fit into the global landscape. For example, international regulations like the General Data Protection Regulation affect data collection, storage and use for organizations doing business in the EU. And as work environments increasingly move to remote or hybrid formats, staff and clients could be operating from anywhere in the world. Cyber threats can also originate beyond the borders of an enterprise’s home country.

4. Build Data Fluency Within

A large part of deriving benefits from data is ensuring your workforce understands the data’s value. The State Department identifies a lack of data fluency and skills among its employees as a challenge. As a countermeasure, the department aims to recruit and train a workforce that will use data-driven insights to further the U.S.’s agenda. 

Data fluency represents an ongoing struggle across most sectors. Incorporating data skills in employee development is a smart move, because it helps organizations retain talent. In addition, employees gain skills to engage in interesting work as automation takes over rote tasks.

5. Hire for a Data-driven Future

The State Department will change its hiring practices so it can include data skillsets in a wide variety of job descriptions.

The strategy is worth considering in other sectors. Chief data officers are increasingly sought after but hard to retain, for example. To keep up with changes in enterprise data tools and management practices, organization must require data skills across different employee roles.

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6. Pilot and Scale AI/ML

The State Department’s efforts to upskill its existing workforce involves piloting and scaling machine learning and AI applications. That process aims to establish the ethical and secure integration of such applications, as well as proper cataloging of the applications’ effectiveness.

Enterprise organizations have often stumbled when scaling AI/ML pilot projects. An Accenture report, for example, found that the scaling of AI was a struggle for about three-quarters of C-suite executives. Ensuring applications provide an ROI has also proven difficult. Getting the necessary data infrastructure in place -- something a digital transformation strategy can help with -- eases the process of advancing data-based pilots.

7. Provide Data Access

Data collection and analytics capabilities are only useful if workforces can easily access the data. The State Department’s enterprise data strategy calls for a streamlined and secure data access process. It marks a shift from its current federated approach to data management. Security will be a key consideration in the transition. 

Cloud applications provide organizations with new options for accessing data, including for remote and hybrid workers -- although security remains a concern. Role definition is a key part of enterprise data access, ensuring that only authorized employees can obtain datasets. In addition, it’s important to train employees on data access practices as part of overall digital transformation efforts.

8. Quality Data, Not Junk Data

Of course, it isn’t enough to simply have data. A well-trained workforce with access to the best analytics tools can’t derive insights if datasets are inaccurate or incomplete. The State Department identifies data accuracy and integrity as a top priority, especially considering the security and privacy concerns around some of the data it handles.

For enterprises, the stakes may seem lower, but data quality can’t be ignored. Investments in data collection and analysis will not show a worthwhile ROI when built on low-quality datasets. Instead, poor data quality will likely create roadblocks for your workforce and slow down digital transformation initiatives. 

9. Think Policy and Governance

Implementing a data strategy before creating a policy and governance framework is like putting the cart before the horse. The State Department identifies policy and governance as core parts of its enterprise data strategy. The aim is to ensure that the department remains at the leading edge of data management and oversight while maintaining an ethical and efficient use of its data.

Effective data governance requires regulatory compliance and ethical considerations. The public is increasingly aware of the value of its data -- as well as the risks when data is improperly stored, accessed and used. While regulatory requirements about data handling already exist, the smart approach is to think beyond those requirements with a focus on ethics, accountability and transparency.

10. Don’t Forget About Security

Understandably, the State Departments takes data security seriously. It has enormous amounts of sensitive data at play, collected from around the world. The department’s enterprise data strategy puts a premium on data sharing within the department, effective data management, ethical data collection and use, and secure data storage.

Public agencies increasingly face cyberattacks, and the private sector hasn’t been spared. The fallout from a data breach can be long-lasting and expensive to deal with. Looming cyber threats explains why about 75% of organizations said they planned to increase spending on data privacy in 2021.

But don’t forget to focus on the security of internal data handling practices. Clear role definition and access permissions help to safeguard data, especially when employees work remotely and/or use cloud-based applications.