How do you innovate with data?
IN this article we’ll discuss innovation with data, and the advent of open use of Global Positioning Systems (GPS) data and how the state of Punjab used data to successfully combat dengue fever. We’ll also look at Open Data as government policy that made it possible to innovate with GPS data and the innovative approach to fighting dengue fever. I intend to throw some light on why innovation with data must be at the forefront of digital and data strategies, if you’re thinking this data driven innovation thing isn’t the most leading-edge technology trend today. If you’re questioning why you would prioritise innovating with data when clearly the latest and greatest trends today is AI and digital everything. Without diminishing the opportunities that digital and AI can deliver if done right, we’ll begin with a comparison between seven-year-olds playing rugby or soccer.
Fashionistas
The top left-hand corner of the quadrant graphic shown above, labelled fashionistas is mentioned in a Massachusetts Institute of Technology (MIT) report as those who love to constantly chase technology trends. This is not too different from seven-year-olds playing soccer. When the ball is kicked in any direction, they all chase the ball in whichever direction as one large bunch of kids. When someone manages to poke a toe to the ball, they all move like bees to honey in a new direction. And they all, most of them, have a good time doing it, but we all know it’s not a really good strategy to good soccer and developing world cup champions.
Governance in this context refers to the business involvement and principles and rules in driving value. And it should not draw to negativity. It is about the guidance and encouragement you get for driving value from data.
The lower left corner in red is what’s called the “losers” in the data value context where there’s no innovation with data, hence no need for governance. And there are more polite terms used by some commentators.
Bottom right corner are the cash cows. There is minimum to no innovation but governance has been in place and the idea is to milk the situation for all its worth until it all runs dry at some point. An example is fixed line telecommunications. They send a bill every month and it gets paid. That’s all profit because the lines under the ground have already been amortised, paid for. The problem is that it’s not a growing marketplace.
The top left corner, the fashionistas, we’ve already covered. The top right-hand corner is for the “digirati” where they’re not just using technology for technology’s sake, but they have a business value proposition associated with every initiative, But technology people, ICT folk, we’re just like the fashionistas — right? “There’s cloud computing!” everybody runs after cloud computing. There’s big data, let’s all run after big data. There’s business intelligence, let’s all run after business intelligence. Data mining, machine language, digital transformation, artificial intelligence, data lakes, let’s all run after this or the other trend.
What happened to Big Data?
Let’s take for example the big noise behind big data, the trend that was going to solve all our problems. We’re going to chase that technology trend, because everybody else is doing it, we don’t know why but it must be fun, it must be worth it. Whatever happened to big data? When was the last time you read an article about it or went to a conference focused on big data?
Perhaps you’ve even invested in it? Was it just yesterday’s fashion? Why are there so many unfinished, incomplete, and under delivered ICT, digital and data projects? It is largely because we’ve taken the technology implementation for the sake of being up with technology trends approach.
For the sake of technology. Failed projects where the business vision is compromised in favour of having technology that works well enough. In the data context it would be collecting data into a storage facility such as a database or data warehouse, accessing that data and producing reports but not necessarily meeting the objectives of the project. Many times, the objectives, the business objectives of the project have not been articulated well enough at a detailed and meaningful level. The technologists take over. As far as they’re concerned the project is a success. Data is captured, it’s stored, it’s extracted into reporting tools which produce beautiful dashboards with graphs and charts. Well, you’re confused. What’s been achieved is a data processing platform and not necessarily a platform that enables business insight.
Open Data
The answer lies in answering the question on any ICT and data project. Why are we doing it, what specifically are we hoping to achieve with this project? Innovation starts when data becomes a resource for the consumer as much as it is a resource for businesses and governments. And this is where several governments have been adopting the Open Data platform as a policy. Not just public data, but Open Data. We’ll discuss the difference later. Let’s first explore two examples of innovation with data.
Open use of GPS data
The GPS project was started by the US Department of Defence in 1973. It was originally limited to use by the United States military. In the 80s after the South Korean Airlines flight 007 carrying hundreds of passengers drifted into Russian airspace by mistake was shot down, President Reagan took the position that the disaster could have been avoided. He maintained that if the Korean Airlines pilot had GPS data available, this disaster would not have happened. That is how GPS data went public - in the interest of aviation safety. And then a huge industry was created around GPS data. It is estimated there are around four million jobs directly associated to the use of GPS data. Today GPS provides critical positioning capabilities to military, civil, and commercial users around the world. While it is the US government that created controls and maintains the GPS system, it is freely accessible to anyone with a GPS receiver.
Fight to eradicate Dengue Fever in West Punjab
An innovative data initiative using mobile devices and GPS in the West Punjab region of Pakistan where dengue fever is a huge issue with thousands of people dying from it. The government didn’t have a lot of money, so they had to figure out a way to fight this dengue fever. They used a combination of crowdsourcing of data using smart phones and other mobile devices. Data analysis was an integral part of the initiative. When people came in to the clinic and were diagnosed with dengue, data was collected via the tablets and phones which allowed the health department to figure out where they were from exactly, where they lived and where they worked. Since you get dengue when a mosquito bites you, that helped identify where the infected mosquitoes were and where the mosquitoes were breeding most.
Data was analysed on where the dengue cases were originating from and then recommend where to pay attention. The big problem was that when you get bitten by a denguecarrying mosquito and later when you get bitten by a healthy mosquito at any other location, that mosquito now becomes a carrier of dengue as well. And it can become epidemic very quickly.
The instant tracking, analysis and identification of new areas of concern was critical to the success of this initiative. So, their strategy was to get rid of the breeding areas, focusing on the most infected areas to the least.
The analysis showed high risk areas and where the mosquitoes were breeding most. Health care workers and community groups and leaders went out with their phones and identified standing water (breeding grounds). They took pictures via GPS or geo-encoded apps and then a bunch of people then “attacked” the breeding grounds and took preventive measures. In some of the bigger water catchments like flooded areas and lakes, the health department poured a special kind of fish that eats mosquito larvae. That made it difficult for mosquitoes to breed in large numbers. The success of this initiative was huge. This was done with no really huge investment. They’d invested in a number of smartphones, tablets and an app. The data was collected and used in innovative ways.
Open Data vs Public Data
The GPS example is one of open data made available to anyone with a receiver. The dengue fever example is a combination of public data made available to people on websites and phone-apps, but also has an open data approach where data is made available in a specific and structured manner to allow ease of analysis and targeted to specific purposes. Public data is the information made available by government and local bodies and businesses in the public domain. It is usually easily available via websites and in the public domain.
It includes datasets and documents that often may only be accessed with a freedom of information request. It may also be made available in non-machine-readable format such as pdf files which makes it difficult to analyse without first passing it through optical character recognition software.
Public data is not always considered open data. Open data is usually a subset of public data. Open data is structured and well-maintained data and is therefore easier to understand, access and consume. Open data is data that is available for everyone to access, use and share.
It can include information about local areas, villages, settlements, provinces, or statistics on the population (census), economy, health, and the environment. If some of these data is only available in pdf or other non-readable formats, then it is considered public data. Open data often detailed to the lowest level of granularity can be downloaded into databases, excel spreadsheets and the like and manipulated. It is protected for sensitive private information and can be anonymised so as to protect individual records.
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