A stronger data analytics democracy is needed. As made evident by this week’s presentation by Tableau on Government Business Intelligence Trends in Boston, there’s a significant opportunity for collaboration between government agencies and private sectors. Nationwide, statewide, and municipal level public sectors have access to data that those in the private sector don’t have readily available. However, given the abilities and technical capabilities of private organizations, these companies are highly-capable of data analytics breakthroughs and can prove to be an asset to government agencies seeking conclusions.
The afternoon presentation proved why and how private and public sectors can mutually benefit from working together for the sake of data-driven decision making. Archetype Consulting’s CEO and Founder, Jason Webster kicked things off by highlighting seven emerging trends in government business intelligence. The theme of his presentation – and in only four words explaining why private and the public need to work together – was that the government is ‘Data Rich and Info Poor.” Jason is on to something – the government has significant data at their disposal but lacks the means on analyzing it and converting it into usable information. This presentation covered seven key takeaways:
Seven Government Business Intelligence Trends
- Modern BI Becomes the New Normal
We can’t revert back to simple data analytics anymore. We need to use everything that we’ve worked so hard to develop, and to make the most out of it. It’s not only the top-ranking, richest businesses that are using data analytics for high-end decision making – smaller companies, non-profits, and even government agencies are using analytics for developing new strategies.
2. The Era of Open Data in Government Arrives
The people wanted transparency, and we got it. By creating and collecting data, the government can now share their data for analysis with non-profit organizations, private sectors, state and municipal level agencies, and individuals. ‘Government creates, private uses.’
3. Collaborative Analytics Goes from the Fringe to the Core
It’s not a wishlist item anymore, nor is it only situationally important. Collaboration is now a neccesity, and a vital part of any major business (or government) decision. This isn’t about pride – sharing data is all for the greater good.
4. Data-Driven Decision Making Explodes in Government
Maybe we’re biased, but we’re happy to see the public sector seeing the potential of data analytics. Making data-informed decisions isn’t solely about business intelligence, as laws and regulations can benefit from more strategic planning.
5. IT Becomes the Data Hero
IT used to be the data farmers, but now modern technological affordances make it easier than ever for John Everyman to be both farmers and decision makers.
6. The Transition to the Cloud Accelerates
The private sector has never been shy about using the cloud, but the public sector has been a bit slower to adapt. We’re starting to see a nice upwards curve of government cloud usage. There are three major reasons why everyone should be using cloud storage:
- Scalability: If your company and/or your data is growing, using the cloud makes it easier to scale.
- Faster/cheaper: All of your data in one spot, with easy access to it. Hard to argue those benefits.
- Infrastructure that we don’t manage: Spending too much time on the IT side just to manage data storage? Using the cloud has an answer for that. Make it someone else’s problem now.
7. Advanced Analytics Becomes More Accessible
Without effort, you can google ‘data analytics software’ and find programs for free or cheap. It’s easier than ever for small companies and individuals to collect and analyze data, and with the government collecting data, all you have to do is go in and make the magic happen. Our Data Analytics program includes training on R Statistical Coding, which is a free software for anyone to use.
It’s refreshing to see collaboration between public and private sectors, especially when it’s for the good of the people, and not for selfish reasons. It’s a win-win situation; privately-owned companies can use a strong dataset, while the government can have their data professionally analyzed by industry experts.
What are some of your favorite examples of data collaboration? What would be your hypothetical points #8, 9, and 10?