Eighty-six percent of federal executives responding to the global Accenture Technology Vision 2018 Survey report their organizations are increasingly using data to drive critical and automated decision-making—and they’re doing so at unprecedented scale.
Industry data bears that out. At all levels of government, total spending on big data and analytics solutions is predicted to rise at a compound annual growth rate of 10.8 percent. For U.S. federal, spending is poised to increase from $3.4 billion in 2016 to nearly $8.6 billion by 2021. (Source: IDC, Government Big Data and Analytics Forecast, 2017–2021: Federal and State and Local Should See Moderate Growth, by Shawn McCarthy, December 2017, Retrieved February 20,2018)
Success with data requires more than spending a lot of money. It also requires a focus on the quality and accuracy of the data being used to produce insights. Left unchecked, the potential harm from bad data becomes an enterprise-level existential threat.
According to our survey, 82 percent of federal executives agree that organizations are basing their most critical systems and strategies on data. Yet many have not invested in the capabilities to verify the truth within it.
Accenture recommends that federal agencies address this new vulnerability by building confidence in three key data-focused tenets:
- Provenance—verifying the history of data from its origin throughout its lifecycle
- Context—considering the circumstances around its use
- Integrity—securing and maintaining data
To meet these demands, every agency must bring together existing data science and cybersecurity capabilities to build a “data intelligence” practice.
Studying data behavior
Behavior is associated with all data origination. That’s true for a citizen applying for benefits online or a sensor network reporting security checkpoints for a transportation system. Federal agencies must build the capability to track this behavior as data is recorded, used and maintained. That provides cybersecurity and risk management systems with a baseline of normal behavior to monitor against.