Through my previous blogs, I have emphasized consistently on the significant value that lies within the data housed in various government systems and records. While there is significant in-house data, a small fraction of the possible value is being realized today. So, the progressive journey that I had shared in an earlier post and illustrated below again provides a practical staged transformation approach that governments can adopt.
This transformation towards the establishment of an Open Data Platform not only drives ease of operations within Government but also promotes innovation from the larger ecosystem. This can be achieved by encouraging participation of Private Entities and General Public to tap into the Government datasets and thereby, creating citizen/resident experiences that would have otherwise been impossible, considering the limited resources at Government’s disposal. While this scenario considers the value that external stakeholders can generate by leveraging Government data along with non-Government data, the converse of this scenario will be the focus of this blog.
The converse is this –
- Government is not the data provider but it is the data consumer
- External stakeholders (Private entities, Citizens, Third parties) are not data consumers but are data providers
- Government taps into the value of Government data + Non-government data
The illustration below extrapolates the 3-stage transformation journey and appends a fourth stage that I call the “Analytics-driven Decision making Platform (ADDP)”. This ADDP can, and ideally should, co-exist with the Stage 3 of the transformation journey, viz the Open Data Platform (ODP). The idea is for the government to tap into its in-house data and correlate that with public data that is available to it (Open Data) and generate value through analytics on the integrated whole. The public data that can be brought on this platform include Quarterly/Annual filings by firms and individuals to Social feeds by residents/citizens/visitors about government services, weather data, media reports etc. Since the in-house data is not going out of Government boundaries, the concerns around data privacy and security are no longer relevant. Such a platform encourages government employees to innovatively think of ways to tap into the data from the larger ecosystem and leverage the same to deliver efficient and effective operations and more importantly, a positive people experience. So, they are not just doing the mundane daily routine but are being given an opportunity to be innovative and push their boundaries – something that you would rarely associate with government employees. Of course, this requires a cultural shift that needs to happen alongside the commissioning of ADDP.
The most significant value of an ADDP initiative is using the analytics to make informed policy decisions and also drive course corrections in real-time. A business scenario of such a platform has been depicted below.
The scenario shows Data at Rest (Historical data sitting in the Databases, Datawarehouses etc) and Data in Motion (Real-time data about events, incidents, status) from different entities like Government, Corporate, Citizens, Media houses, Weather etc. It is obvious that if this broad spectrum of incoming data has to staged on the ADDP, one has to be considerate of the Four Vs of data – Volume, Velocity, Variety and Veracity. The platform should be able to gather data that is unstructured or structured, real-time or static, machine readable or non-machine readable, clean or nonsensical and from thereon identify data that is relevant in a certain government context. This needs to be facilitated by a reliable Big data platform with strong analytical capabilities.
Here’s an example – Imagine that the Ministry of Education wants to make a decision whether the subsidized education scheme that has been operational for last 3 years should be continued from the coming financial year onwards. Traditionally, this would be done by tapping into Government’s historical records to see the success and outreach of the scheme in terms of its adoption rate across the country. While this is an important parameter, combine this with
(a) what the citizens or the school administrations have been saying about this scheme on social media
(b) what the media houses have been writing about it
(c) correlate that with improvement in employ-ability rates that has been tracked by the Ministry of Labor studies and
(d) correlate that with financial burden on the exchequer tracked by the Ministry of Finance
(e) combined with what the UNESCO publishes in its “Global Education Digest” report about the status of child education in the country
Such aggregation of datasets from various sources gives a holistic view that can then be analyzed by drawing correlations between various perspectives and provide insights that would otherwise be unavailable. The Government, viz their internal workforce, should be entrusted with the responsibility to identify the nature of datasets that are required to achieve the comprehensive picture. The government employees are best positioned to identify the lacunae in existing information and with the ADDP platform, the get a rare opportunity to be creative and innovate.
Between Stage 3 (ODP) and Stage 4 (ADDP), governments would ideally want to adopt the ODP approach first but there is no stringent requirement to do so. So, while it is not absolutely necessary to have ODP and ADDP done in a sequential manner, these initiatives are complementary and should ideally co-exist. Each of the four stages of the transformation journey brings unique value as they are realized.
It must be noted that governments worldwide are yet to reach this stage of informed decision making through a data platform. However, in this age where gigabytes of data are generated at the wink of an eye, there is immense potential in such a platform. While ODP initiatives has been picking up steam worldwide and are widely published and talked about, there are very limited initiatives to establish an ADDP and the known few are in their nascent stages.
This ADDP stage requires a huge transformational shift internally but the incentive to get there is unprecedented.
Note: I presented on the topic of Open Government Data at a conference held by The Open Group in Feb 2016. This presentation summarizes the posts from my blogsite.