{"id":17561,"date":"2016-11-18T17:58:11","date_gmt":"2016-11-18T22:58:11","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/data-in-schools-learning-from-inblooms-failures\/"},"modified":"2016-11-18T17:58:45","modified_gmt":"2016-11-18T22:58:45","slug":"data-in-schools-learning-from-inblooms-failures","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/data-in-schools-learning-from-inblooms-failures\/","title":{"rendered":"Data In Schools: Learning From InBloom\u2019s Failures"},"content":{"rendered":"

Education is an industry where data analytics has a lot of potential but has been slow to pervade. The amount of data a school district tracks about its students is enormous. This data, while hard to maintain, provides a huge opportunity to deliver personalized learning: a student can get the teaching and support tailored exactly to his\/her needs. However, consolidating and making sense of this data is a very challenging proposition for schools and is not a part of their core competencies [1].\u00a0The data is usually messy with no standardization between various databases within a school; the attendance database could store data very differently from the grades database. Among different schools, data formats vary even more.<\/p>\n

In 2011, the Bill and Melinda Gates Foundation and the Carnegie Corporation of New York, provided a $100 million grant to InBloom, a non-profit, to tackle this massive technological challenge [2]. InBloom promised to create value for schools by taking all the data about each student stored in fragmented data stores, massage it into a uniform format, store it in the cloud protected by world class security standards and then use it to populate easy to use dashboards [3]; teachers could then use the dashboards to track each student\u2019s progress on various academic and non-academic dimensions and deliver personalized learning.<\/p>\n

\"inbloom\"<\/a>
A sample student dashboard InBloom created using fake data to showcase its technology [3]<\/figcaption><\/figure>While most states planned to share data only from selected districts, New York and Louisiana promised to share data from the entire state [4]. Cleaning and consolidating this data opened the doors for many other providers to use it to power other learning applications and easily deliver them to all schools on the InBloom platform. The entire platform was going to be open source for anyone to understand and contribute to. The edtech industry was buzzing with joy [2]. Unfortunately, this glee was not meant to last.<\/p>\n

InBloom soon started to get immense backlash from parents who were uncomfortable with the idea that all their child\u2019s data was being shared by the school with a third party. Parents and privacy advocates argued that the sensitive data could be sold by InBloom to marketers [3]. Moreover, a lot of parents believed the cloud was unsafe and data could be stolen by \u201chackers\u201d. Since personalized learning was so nascent and the technology not established, the general sentiment was that the risks greatly outweighed the benefits [5]. So strong was the reaction that within two years, three states pulled out, one put its data on \u201cindefinite hold\u201d and three said they never planned to share any personal data in the first place. The final blow came when New York passed legislation prohibiting the state department from giving data to aggregators like InBloom, causing New York, the largest project, to back out. Within three years of launching, InBloom decided to shut down its operations [3].<\/p>\n

In examining some of the root causes of InBloom\u2019s failures, there are a few things it could\u2019ve done differently to avoid the downfall.<\/p>\n

    \n
  1. There was a significant lack of trust between InBloom and its various stakeholders. In most states, data was being shared with InBloom without any parental notification or consent, and without allowing opt out [6]. InBloom left the job of assuaging any privacy concerns to school districts. Further, InBloom maintained the right to sell the data to other providers. InBloom could have worked more closely with school districts in addressing these concerns and clearly indicated that the data would only be used for facilitating learning, and not for advertising and marketing applications.<\/li>\n
  2. InBloom could have helped assuage the security concerns. Despite an independent third party audit that InBloom was safer than many existing systems in use [7], parents still believed the provider was insecure and InBloom made no efforts to change this. InBloom remained extremely apathetic to all security apprehensions raised and came across quite arrogant in all these interactions.<\/li>\n
  3. Instead of going all out and getting many states on board, InBloom could have started with a pilot site and built an application that teachers in the site could have tested out to see the benefits. Involving teachers and schools as thought partners would\u2019ve also helped them get advocates for their cause in the community when things got rough.<\/li>\n
  4. Similarly, InBloom could have restricted the amount and types of data they required initially, and gone for \u2018small and actionable\u2019 data [7] over \u2018big data\u2019. The InBloom database included more than 400 fields about students, some of which were very intimate such as family relationships (e.g. \u201cfoster parent\u201d) and reasons for enrollment (e.g \u201cleaving school as a victim of a serious violent incident\u201d) [4]. In initial applications, sensitive fields could have been omitted.<\/li>\n<\/ol>\n

    Overall, InBloom\u2019s failure demonstrated the overarching lesson that in industries that are slow to adapt to technological change, organizations need to be quite thoughtful, deliberate and engaged when trying to roll out digital transformations.<\/p>\n

    \n

    Word Count: 798 Words<\/p>\n

    Bibliography<\/strong><\/p>\n

    [1]\u00a0Lorna\u00a0Earl,\u00a0Steven\u00a0Katz, Leading Schools in a Data-Rich World, Second International Handbook of Educational Leadership and Administration, 2002.<\/p>\n

    [2] \u00a0With $100M From The Gates Foundation & Others, InBloom Wants To Transform Education By Unleashing Its Data, TechCrunch, February 2003,\u00a0https:\/\/techcrunch.com\/2013\/02\/05\/with-100m-from-the-gates-foundation-others-inbloom-wants-to-transform-education-by-unleashing-its-data\/<\/p>\n

    [3]\u00a0InBloom Student Data Repository to Close, The New York Times, 2014,\u00a0http:\/\/bits.blogs.nytimes.com\/2014\/04\/21\/inbloom-student-data-repository-to-close\/?_r=1<\/p>\n

    [4]\u00a0What the Failure of InBloom Means for the Student-Data Industry, The Citizen\u2019s Guide for the Future, 2014, http:\/\/www.slate.com\/blogs\/future_tense\/2014\/04\/24\/what_the_failure_of_inbloom_means_for_the_student_data_industry.html<\/p>\n

    [5] InBloom’s Collapse Offers Lessons For Innovation In Education, Forbes, 2014, http:\/\/www.forbes.com\/sites\/michaelhorn\/2014\/12\/04\/inblooms-collapse-offers-lessons-for-innovation-in-education\/<\/p>\n

    [6]\u00a0InBloom Background, Parent Coalition for Student Privacy, http:\/\/www.studentprivacymatters.org\/background-of-inbloom\/<\/p>\n

    [7]\u00a0Privacy Fears Over Student Data Tracking Lead to InBloom’s Shutdown, Bloomberg, 2014, http:\/\/www.bloomberg.com\/news\/articles\/2014-05-01\/inbloom-shuts-down-amid-privacy-fears-over-student-data-tracking<\/p>\n

    [7]\u00a0The Real Lessons from InBloom, IMS Global Learning Consortium, 2014, https:\/\/www.imsglobal.org\/article\/real-lessons-inbloom<\/p>\n","protected":false},"excerpt":{"rendered":"

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