Data Driven Innovation - A Primer

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Protecting against poor uses of data and supporting good ones. Piloting a data trust.

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2014: The Age of Data-Driven Storytelling, A Primer

Nesta Blogs. The following are a few blogs around the issues of data, privacy and innovation. Data Driven Innovation ". A Primer on Civic Digital Trusts. About This Primer. In a Nutshell. Smart Cities. What is a Smart City? The Quayside Development in Toronto. The Need to Govern the Digital Layer.

From the Citizen's Point of View. What is a Trust? What is a Civic Digital Trust? Examples of Civic Digital Trusts.

Aspirations for a Civic Digital Trust. Design Principles for a Civic Digital Trust. Technical Architecture Options. Business Model Options. Concerns and Open Questions. Use Cases.

About OPSI - Observatory of Public Sector Innovation Observatory of Public Sector Innovation

Sharing Energy Usage Data. Sharing Building Space Data. But, it is a bit trickier than that. DDI requires some careful understanding of how data works and how it could be used to get insights. Therefore, place where it should start is important. The best starting place for DDI could be around project managers, or if your organization is big enough to accommodate project management office, for agile companies, it should be around group leads.

About OPSI

In short, DDI should start from a place that is not a stranger to data and understands how to handle it. So, in short, it could exist everywhere but it should start from a place that provides the most amiable surroundings required by a data driven project. Project managers, supervisors, PMOs are meant to keep a tap on the progress, so they possess some basic skills to function as data driven professionals and therefore, could help the best in understanding and executing a good DDI strategy.

When is the time to delve into DDI?


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In short, the sooner the better. DDI requires substantial amount of preplanning and dedication. The sooner organizations delve into data driven innovation, the better will be its execution and value to the organization. A good data driven innovation implementation requires some practice and iterations on data models, validations, analysis and reporting. So, a successful implementation will rarely emerge from first implementation and would require some iteration.

Also, the sooner the organization will start in direction of implementing DDI, the better it is because organizations will start acting in ways to facilitate smart data handling, which will have its own benefits. But, one caveat is that organization should have data to play with. Doing DDI sooner when data handling capabilities are not established could confuse the processes and steer the implementation in wrong directions.

Boardroom to Conference Room to Cubicle

To summarize, DDI is important and beneficial to any organization. It has the tendency to make any organization grow sustainably without having to invest too much into research and development. It support continuous improvements and that too without investing too much money and it could re-utilize the same infrastructure for sustainable leanings. Tags analytics big data bigdata data driven design datadriven datadrivendesign Design.

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