Data is a business asset that can advance agencies’ missions, or serve as a drag on effectiveness.
The last decade has seen an explosion in both the amount of data available to federal organizations and the range of tools available to harness it. The cloud, machine learning, artificial intelligence—the possibilities seem endless. In spite of these opportunities, many federal executives find themselves struggling with how to turn raw data into useable information. Reports accumulate but do not always answer the most relevant or pressing questions. How can an executive turn his or her data into the vital agency asset that it should be?
Data now drives both the operational and non-operational sides of public organizations. U.S. Cyber Command obviously uses data to drive its day-to-day mission, but what is often overlooked is how important data is to the support side of government agencies. The support divisions, or business owners, need to be using data just as much as those who are performing a direct mission function. While each agency needs to directly assess and improve its data usage on the mission side, there are often overlooked strategies that can be used to drive support functions more effectively across all organizations, ultimately having significant impact on the mission. Here are two brief examples:
Finance and Audit
Many agencies spend the same amount of time and resources on their compliant employees as those who are out of compliance on credit card purchases, travel vouchers, etc. With a robust financial audit system, anomaly detection and outlier analysis can be effectively implemented to predict which expenses (or employees) need the most attention, potentially freeing up resources. CFOs can use data on travel vouchers and credit card purchases to monitor policy compliance as well as focus audit resources on outliers that potentially represent evidence of a compliance issue. Purchases can be monitored by type and time profile to assure that resources are being allocated to support the agency’s mission.
The audit process is also an area ripe for improvement through the application of data and analytics. Audits are generally considered a distraction that consumes resources, but do not provide an offsetting value. The largest driver of audit time and cost is the manual nature of the analysis. Using automated data feeds and other iterations of robotics and artificial intelligence, regular or real-time reporting can not only lower personnel costs and increase efficiency, but can also support a much more robust audit function that leads to better audit results, saving organizations money and reducing institutional risk.
The Human Resources function is a prime example of the importance of strategically managing data. One third of government employees will be eligible to retire by the end of this year and many agencies are facing an environment of shrinking resources along with increased mission requirements. Agencies must be able to match the skills of the workforce nearing retirement to those that are critical for the mission. This is a great example of a gap that can be closed with the strategic utilization of operational or mission data for support functions. Strategic workforce planning is a holistic program of gathering and deploying data to build models that allow agencies to answer these types of key questions quickly and effectively.
Where to Start?
The first step for federal executives is to become an informed consumer. While some data problems can be solved by a large systems investment, this is never the best first step. There are a large number of low cost or free tools that allow business owners to access, assess, clean and analyze data from a variety of sources. This provides short-term benefits but can also have long-term impacts. Even if investing in a new system is ultimately deemed the right step, the work put in by the business areas to understand the data will pay dividends in system implementation.
Applying a new system to poor data provides fast access to bad data, and few benefits to the organization. By understanding the data, management can be equal partners in designing how the data will reside on the system, and how it will drive agency goals and decision making. From there, it may make sense to hire a lead data scientist or data analytics team. The demand for data scientists, or people with experience in data science and analytics, is far greater than the current supply, and that trend is expected to rapidly increase.
Every organization is different, so the data management solution should be tailored to current and future needs. It is also important to get involved in the organization’s data governance process, which covers both the mission and support sides of data management for departments and agencies. Many aspects of data governance belong to the IT shop, but business owners need to own data quality for two reasons. First, only business owners can really interpret quality. IT shops can monitor the data creation process, but the most effective way to assess quality of the data is to use it and interpret the results. This is the province of business owners and analysts. Second, it is business owners who pay the price for inaccessible, inaccurate or undocumented data. Whether the cost comes through as ineffective workforce management or poor cyber security, the costs of sub-optimal data management are borne by business owners.
Data is a business asset that can propel agencies’ missions forward, or serve as a drag on their effectiveness. This realization must be driven by the business owners and encompass both direct and non-direct mission support functions if it is to take root in the organization. This is not a small undertaking, but the benefits across the organization can be huge. What is your agency capable of accomplishing by using data effectively?
Justin Schoolmaster is a director in the homeland security and law enforcement practice at the professional services firm PwC.