You know the old saying about a boat: The best days for a boat owner are the day they buy it and the day they sell it.
In many ways, data analytics programs create the same reaction. There is untold enthusiasm at the start of an analytics venture, but due to a wealth of reasons, the trough of disillusionment strikes and the emerging results too often fall short of expectations.
Robust data analytics present federal agencies with the ever-promising potential to make better decisions, streamline operations, mitigate risk, enhance security, and improve citizen services. The challenge comes not in the data analytics but in how agencies – and most organizations, regardless of sector – struggle to turn data into actionable information.
These organizations commence on a data analytics journey with the best intentions. Disappointment strikes, though, due to a lack of a clear vision for the role of analytics and what exactly they want to achieve. Analytics itself is a tool that used in the right ways can provide a tremendous impact. When misused, analytics work just about as well as using a hammer to fix a hole in a sinking ship.
How to Set Up Analytics for Success
The value of an analytics program gets determined before the effort truly starts. When deciding to pursue analytics, organizations need to think ahead to the end problem they want this technology to solve – the omnipotent ‘why’ question!
This is especially true for government agencies that each hold tremendous amounts of important data. They must decide what mission challenges data analytics can address, and how to reach an end point that resembles success. To that end they will then decide:
- What is your leading priority for this data analytics program?
- What are the day-to-day pain points we want to solve?
- Is there an already existing solution to tackle this challenge?
- Do we have the needed data or do we need to find it?
Answering these mission-domain questions in partnership with a data scientist can create a strong momentum for each effort.
Data analytics programs often fail because they lack this clear trajectory. Organizations frequently launch data analytics programs to maximize the data they have on hand, feeling that if tied to analytics they will gain efficiencies and insights that were previously unknown. It is this method, though, that leads to failure.
Like many technologies, data analytics is not a silver bullet to success. It is a tool – a very powerful tool – that when used correctly can provide amazing value. That value will not come on its own, however, and organizations must make the time investments to strategically align and continuously innovate analytics programs with mission values.
The Government’s Need for Analytics
Government agencies collect and hold large amounts of data on nearly every aspect of life from health and education to money and transportation with everything in between. The potential for data analytics remains monumental but also critical to success.
Federal agencies continue to fight the Silver Tsunami: the ongoing wave of retirement-eligible employees that promises to drain each agency’s institutional knowledge. These team members have untold domain knowledge of agency missions and day-to-day operations that must get collected and recorded. That data alone can provide valuable insights into overall functionality, providing untold opportunities to leverage automation and organizational efficiencies to lessen the impact of their departure.
There is also the need to ensure the proper stewardship of taxpayer dollars. Data analytics, when used correctly, can provide agencies with large efficiencies that improve the impact of government programs. Data analytics can improve performance down the program level, providing taxpayers with a larger return on their investment.
A Data Analytics-Filled Future
Data analytics projects fail from a lack of preparation and a clear vision. When starting an analytics program, do not put absolutes on yourself that may ultimately harm its success. Too often, organizations try to stand up a program within a few months and in their rush fall short of critical planning actions.
Take time with analytics programs. Unknowns will always creep up and unexpected situations will emerge. Be prepared for those possibilities (intentionally avoiding referencing these as roadblocks and the negative energy associated with it) and keep an open mind. That may include changing the scope of an analytics program or shifting from the original thought. Allow for the data and interim findings from the experiments and the solution exploration to lead the way.
Data analytics does not need to be like that old boat. Plan ahead and your data analytics program will continue to provide positive results.
