Posts with the tag
“Big Data”
Disrupt and Innovate in a Data-Driven World
If you do an internet search for ‘data-driven disruption’ you can find articles about almost every industry being disrupted by digitalisation and new applications of data. Banking, transportation, healthcare, retail, and real estate, all have seen the emergence of new business models fundamentally changing how customers use their services. While there are instances of data-driven efforts in the nonprofit sector, they are not as widespread as they can be. Bridgespan Group estimated in 2015 that only 6% of nonprofits use data to drive improvements in their work.
At the same time, the Sustainable Development Goals (SDGs) have set a very ambitious global change agenda and we won’t be able to meet their targets by doing business as usual. To achieve the SDGs requires new ideas across the board: new solutions, new sources of funding, new ways of delivering services and new approaches to collaborating within and across social, public and private sectors.
The private sector already very successfully uses data analytics and machine learning not only to realise efficiency gains but also – even more importantly – to create completely new services and business models. For example, applying machine learning to wind forecasting is expected to reduce uncertainty in wind energy production by more than 45% and will allow utilities to integrate wind more easily with traditional forms of power supply. And entirely new utility start-ups such as Drift use machine learning technologies to provide customers with cheaper wholesale energy prices by more accurately predicting consumption.
In the nonprofit sector, early applications of data analytics and machine learning have mostly focused on improving fundraising and marketing. In a next step, the broader adoption of data analysis techniques and tools has the potential to help nonprofits increase their programmatic impact as well as identify completely new ways of achieving their mission.
- Gain improved intelligence on operating context and needs through expanded use of descriptive analytics techniques. On the program side, teams largely tend to use descriptive analytics – statistical techniques that provide insight into the past and answer: “What has happened?” – on survey data, sometimes complemented by samples from larger raw datasets, e.g. Facebook posts or tweets. In many settings this is the best information available. However, it presents obvious drawbacks: given the expense and time required to conduct surveys we frequently operate based on information that is years old. Also, surveys are often run to confirm or refute certain hypotheses making it challenging to utilise existing survey data to answer new sets of questions. The more we can directly analyse raw data, such as today’s internet searches, the more we will be able to obtain a close to real-time picture of the situation on the ground. Applying data analytics and machine learning to large raw datasets will likely also yield us new and unexpected insights as these techniques and tools allow us to unearth patterns and seek potential explanations for those in contrast to responding to a predefined set of questions.
- Identify those most at risk or most affected by a problem more accurately by using predictive analytics. For example, a County Department of Human Services in Pennsylvania recently implemented a predictive risk model designed to improve screening decision-making in the county’s child welfare system. The model integrates and analyses hundreds of data elements. The resulting score predicts the long-term likelihood of home removal and provides a recommendation on whether a follow-up investigation is warranted. The model has been shown to be effective in preventing the screening-out of at-risk children. It has also lowered the number of investigations with potential disruptive effects on low-risk families. One could imagine similar models being applied to screening cases of domestic violence or abuse of domestic migrant workers.
- Achieve best possible outcomes for individuals through the application of prescriptive analytics. In healthcare, some hospitals are now generating predictions of a patient’s readmission risk at the time of diagnosis. Patients with a higher likelihood of returning to the hospital within a month receive additional care and supports such as home visits. This has reduced the readmission rates and freed up resources that can be used to treat additional patients. There are many possible use cases for prescriptive analytics in the development sector, particularly in health where we have much existing data on what works in light of specific risk factors. Tools that incorporate these models could assist community health workers in triaging cases and prioritising their workload. They could also be applied to people suffering from addictions or people with learning challenges to prescribe individualised treatment and support plans.
As these approaches become more mature and wide-spread in their application their impact will go much beyond making workflows more efficient. They have the potential to fundamentally disrupt how we work and what we define as our core competencies. Today, it may seem challenging to move towards a future where recommending who to support and how could be largely automated. I also don’t want to minimise the challenges in this scenario: the availability of required data and the privacy issues involved.
However, I want to encourage us to actively embrace and shape this future as its potential for positive impact is immense. We need to work together to ensure that the automation involved in these techniques and tools will provide valuable insights that support humans in making thoughtful and effective decisions, free up our valuable and constrained resources and focus them on those parts of our work that truly make a difference in people’s lives.
Claudia Juech
Executive Director
Claudia Juech is the founding Executive Director of the Cloudera Foundation, which will use Cloudera’s expertise in data analytics and machine learning to change people’s lives for the better. Previously, Claudia was an Associate Vice President at the Rockefeller Foundation, leading the organisation’s Strategic Insights division. Working with grantees and partners around the globe, she and her team used data and information to identify large-scale opportunities to address economic inequality and critical challenges in the areas of health, the environment, and in cities. Prior to joining the Rockefeller Foundation in 2007, Claudia was a Vice President at DB Research, Deutsche Bank’s think tank for trends in business, society and the financial markets. She has a degree in Information Science from Cologne University of Applied Sciences and an International MBA from the University of Cologne.
How are Blockchain and Big Data currently being used in the civil society sector?
The International Civil Society Centre is hosting its second Innovators Forum on 27-28 February 2018. The Forum will explore the benefits and possible uses of Blockchain and Big Data in the civil society sector. Before the Forum, guest authors will dive into specific examples or innovations around digitalisation and digital technology, in this week’s blog we want to give a brief overview of the main terms and some examples of their uses.
Many CSOs around the world have realised the potential linked to both Blockchain and Big Data and are currently experimenting with how these technologies can support their work.
BIG DATA – WHAT IS THAT?
The term Big Data refers to extremely large datasets that can be analysed for trends and correlations by connecting different data on a large scale. Due to the size and complexity of the data sets used, new links and patterns can be uncovered. This means that problems that were previously not possible – or simply too complex! – to explain can now be tackled. Most CSOs work with Big Data to improve knowledge about marginalised or ignored groups of people and to identify better ways to serve them. Here are three examples of how:
COLLECTING BIG DATA
Plan International is leading the way in developing a digital birth registration tool. Its aim is to help register the millions of undocumented births around the world to lay the groundwork for better health care, education and access to other government services. The system draws on mobile phone technology to reach people and places that governments fail to document, mostly due to the lack of resources.
USING BIG DATA
Caroline Buckee, a Harvard University epidemiologist, used the data of 15 million mobile phones in Kenya to demonstrate how human travel patterns contribute to the spread of malaria. Based on this data, she helped pinpoint where best to focus government efforts to control malaria.
CONNECTING THE DOTS OF BIG DATA
The Centre-hosted project Leave No One Behind is combining smaller data sets to help achieve the Sustainable Development Goals (SDGs). Using evidence collected by ICSOs in four pilot countries, the goal is to identify the drivers of exclusion in local contexts, and support joint advocacy that will encourage governments to be accountable for their SDG promises.
BLOCKCHAIN – WHAT IS THAT?
Blockchain is a network technology can complete any kind of transactions or verification processes in a transparent way. It is a distributed ledge that everyone can view. Thus a transaction, sending a data block (hence the name), is viewable to all and not reversible or modifiable, making Blockchain transparent and accountable.
Many CSOs and social entrepreneurs are using Blockchain technology to increase the efficiency of their operations or increase accountability around the social issues they aim to tackle. Here are a few small examples:
TRANSFERRING FUNDS FASTER AND CHEAPER
Disberse facilitated the transfer of donations to a school in Swaziland using Blockchain-based technology, saving £375 in international bank transfer fees. The United Nations World Food Programme distributed cryptocurrency-based vouchers to 10,000 Syrian refugees in Jordan.
INCREASING ACCOUNTABILITY IN SUPPLY CHAINS
Blockchain can be used to track and verify interactions between different actors around the globe. Bext360 and Fairfood International aim to ensure fair wages and prices for producers and farmers by monitoring the entire supply chains of coffee, coconuts and other products.
These are just a few examples of the way Big Data and Blockchain are being used to innovate in the civil society sector and beyond. We want to discover more ideas, case studies and stories with our partners, colleagues and friends from across civil society. We also want to look at some of the challenges that come with the use of these technologies: How do we ensure that data is properly secured and not misused? How do we design projects in an inclusive way and increase the number of people who benefit from technological opportunities?
The Innovators Forum will be a starting point, but we will cover different aspects of digitalisation and digital technology through the year 2018. If you want to get involved or share your own work in this space, get in touch!
Thanks to Bond for the inspiration for this article.
