AI for the Enterprise

Mine public and private data to gain broader context and make better decisions

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Key Points:
– It’s critical for many businesses to get a unified “single pane of glass” view of private business data alongside publicly accessible data.
– Companies are adopting technology to compare private business data with third party and open data.
– Unlocking insights from private business data is valuable. Contrasting these with open data is invaluable.

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The digital age has enabled greater visibility and access to data and content than ever before. Students, research professionals and businesses benefit from data democratization in ways that would have seemed impossible even a decade ago. Government entities, associations, educational institutions and even for-profit organizations are generating and sharing information like never before via multiple channels and formats including

  • Social media
  • Community of practice portals and extranets
  • Streaming or recorded videos and podcasts
  • Whitepapers, ebooks, reports and other thought leadership content
  • Government agency reports

Though some businesses are still striving to eliminate departmental silos within their enterprise, leading organizations are adopting technology to compare and contrast their private business data with third party and open data from the digital realm.

According to the Open Data Institute, “Open data is data that anyone can access, use or share” without infringement of copyright, patents or other intellectual capital controls.

The opportunity is now within reach for a unified “single pane of glass” view of your private corporate data, alongside publicly accessible data from the internet. Cognitive technology enables data unification and analysis, also allowing for aggregation of relevant, timely data points like industry news. These data points could be driving market behaviors, and need to be considered in making strategic decisions.

Unlocking insights from big data within your enterprise is valuable. Contrasting these insights with open data is invaluable.

Here are three ways that information management leaders can leverage the nexus of private and public data to drive business value:

1. Enhance product design and engineering

Consider the automotive manufacturing industry. Product lifecycle management in the car business has always played a crucial role. For example, product managers at a car manufacturer could review data such as vehicle model sales, safety and/or warranty service statistics relative to customer sentiment on social media, the EPA, or reviews from automotive journalists. They could incorporate information gathered from the Internet of Things such as exhaust emissions or how many times OnStar dispatched emergency services when an airbag was deployed.

By comparing internal data with open data, companies can make strategic product roadmap decisions in context with online customer feedback, industry trends and the direction their industry is headed.

2. Improve product safety and save lives

Manufacturers have to leverage all their data and external data to identify issues as quickly as possible to get ahead of avoid negative press, expensive product recalls, huge penalties by industry regulators, millions in legal liability, and most importantly, they need to protect the safety of their customers. It’s critical for manufacturers to identify reactions to new products early, especially negative feedback and to effectively address customer perceptions and concerns as soon as possible by making sense of ALL the data, structured and unstructured, private and public, that’s available to them.

Structured data often exposes the “who,” “what” and “when” of a problem. But the “how” and “why” — often the root causes — are buried in unstructured content. For example, automobile manufacturers can effectively harness text analytics on vehicle safety data to diagnose recall issues through publicly available data. Auto manufacturers can isolate and pinpoint the cause of safety issues through publicly-available data from the National Highway Traffic Safety Administration (NHTSA) through basic out-of-the-box analysis tools. The same concepts can be applied to other industries and issues where unstructured or text-based data is available to manufacturers.

Natural Language Processing models can be created by subject matter experts at companies (not just programmers or data scientists), to effectively dimensionalize abstract concepts. This allows more teams and employees to ask questions of the data that wasn’t possible before as standard text analytics and search technology couldn’t deal with the variability in natural language text.

3. Supercharge competitive intelligence

You could take the same car manufacturer scenario above a step further, and envision how product managers could benefit from contrasting their business performance data with news and insights available about their competitors in the public domain, such as recalls, or new model announcements.

Open data exchanges and resources like AngelList can empower startups to access sources of funding, create partnerships and find skilled talent so they can compete with larger, established players in their industry. The World Bank also offers open data resources to companies around the world to augment their data repositories with open data.

In addition to collecting their own data, organizations can tap into a wide spectrum of public or open datasets. For example, a data science consultant Max Schron collaborated with the World Bank to study poverty in Bangladesh. Traditionally, study data was collected every five years by people going door-to-door which was expensive and time-consuming.

Another example is Polynumeral, where they used freely available satellite data from the National Oceanic and Atmospheric Administration (NOAA) to examine nighttime lighting patterns and water quality observations from across the country. The historical survey data could be compared with the satellite data to ensure accuracy and understand trends over time better than household surveys, which weren’t always reliable.

4. Improve quality of customer service and patient care

Service-based organizations like healthcare companies benefit significantly from juxtaposing internal data with open data. Consider how the Cleveland Clinic is using genomic data to find better treatments for cancer patients. The clinic can analyze findings from their own patient cases alongside data from other cancer research and treatment centers. The US Food and Drug Administration (FDA) offers a wealth of open data resources on medical devices, pharmaceuticals and foods for researchers and developers to use at their discretion for mobile applications, product engineering and other research purposes. IBM and the FDA have also partnered to define a secure, efficient and scalable exchange of health data using Blockchain technology.

Though blockchain encryption is meant to authenticate users as opposed to making data openly available, it does provide greater access to data like anonymized medical records, clinical trial data and other health information. Hospitals and clinics can benefit from decades of the FDA’s stored data on medical devices, drugs and food safety. Patients will benefit from easier access to their health records. Providers can leverage broader access to patient case histories to better diagnose and treat ill patients based on learnings from millions of case files and research journals, as well as their own case data.

5. Information transparency can increase efficiencies

Though the value of intellectual capital will always remain high, many companies are driving business results by sharing conservative measures of their data in the open data sphere. Information exchanges between partners and suppliers, and participation in industry analyst reports are a few ways where information transparency can increase supply chain efficiencies and customer engagement. Many companies use their data in whitepapers and reports to demonstrate thought leadership and experience. Others leverage it to meet financial or environmental regulatory requirements.

Through side-by-side comparisons of private/proprietary and public/open data in a single in-depth view, information management professionals and business leaders can validate their data quality, and reinforce the basis of their decision-making. Public-private partnerships, like the IBM Watson “Smarter Cities” initiative rely on open data to provide guidance to similar projects that follow. Corporations, governments and NGOs reuse the learnings of successful smart city projects for the benefit of constituent taxpayers, and to create business cases to effectively budget for such initiatives.

From data into insights with Watson Discovery Service:

If you are looking for ways to aggregate public and private data, and effectively present relevant data with greater ease and speed, Watson Discovery Service offers a comprehensive set of developer APIs to make that goal a reality.

Extract value from your private data as well as publicly available and third-party data by converting, normalizing and enriching it with integrated Watson APIs. Try Watson Discovery Service for free to get started today.

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