The Data Divide—And How to Cross It

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Data Divide, AmazonTsunamis are caused when the tectonic plates that lie at the base of the ocean shift. These movements cause earthquakes. Sometimes the tremors of the earth cause a tsunami, like the one in 2011, which ripped open the Fukushima nuclear reactor in Japan. That tsunami may have signalled the arrival of digital tech, an equally potent upheaval that will change the world of work.

The mobile revolution has already created a hyper-connected world. This has enabled the explosion of social media and led to the popularity of cloud technology. Just as mobile devices have connected humans, sensors are increasingly connecting the devices that surround us. From our cars to thermostats and beyond, every surface has the potential to be embedded with sensors and connected to each other. A world of connected devices with human beings acting as the nodes will generate millions of terabytes of data every second.

Over the last few years, while some leaders have picked up the weak signals about the data explosion that is here, 2017 will be the year of the Data Divide. On one side of the divide there will be a small but growing number of organisations that are building their capacity to crunch this data by using artificial intelligence. On the other there will be those who live with traditional HRIS reports created by using spreadsheets. If you can still crunch your organisation’s data on a spreadsheet, you are missing the opportunity.

The business and talent agenda must be drawn from insights supported by quantitative and qualitative data. The data sources can be structured or unstructured. Data is generated from a one-off interaction or in real time on a continuous basis. Sensors form the basis of real time data.

For example, Amazon draws on real-time data to classify books in its brick-and-mortar stores very differently than does any other bookstore. Their categories are based on data collected from millions of transactions on their websites. Their categories are:

  1. Books with more than 10,000 reviews on Amazon.com
  2. Fiction top-sellers in Boston
  3. Highly rated fiction on Goodreads
  4. Books Kindle readers finish in 3 days or less

When Amazon opened their bookstore in Chicago, they knew what to stock up that Chicagoans loved. They knew that readers in the city love biographies. The cooking and travel sections will be popular draws for the city. Amazon has used the data collected from its online purchases to know that Chicagoans seek travel advice about Florida, the Caribbean and Midwest states like Ohio and Michigan.

Real time data can prove invaluable in other ways, too. Getting real time data about the usage of office space can lead to a decision by an organisation to invest in or spin off expensive real estate. Getting real time data on interaction patterns among employees of different departments can give deep insights about the levels of collaboration and innovation in the organisation.

Collaboration and empowerment

Leaders can tap into a common data pond made up of multiple sources and multiple methods of gathering real-time data. Access to a common pool of data across functional silos can best be leveraged when the leaders of the organization start working in a boundaryless manner. They have to stop thinking in functional silos. The entire C-suite can collaborate and decide to launch a new incentive system by examining the decision from their various individual lenses. Executive teams will have to be far more collaborative in the new world.

Data drawn from a common data pool can be used to empower the people in the field, as well. A salesperson can look at the impact of a discount on the bottom line in real time. And the marketing team can judge in real time if a campaign is impacting customer behavior.

Data can be leveraged by different people in different specialties to solve real-world problems. A neurogeneticist is working in an e-commerce start-up to solve the problem of how to plan a delivery route across the busiest parts of the city. He is building his algorithm to mimic the way human genes convey information. A competitor, meanwhile, has hired a nuclear physicist who worked in the Large Hadron Collider to solve the same problem. Both are approaching the challenge as a data problem, after all.

How to get started

Here is what you can do to cross the data divide:

  1. Define your stakeholders and data sources (i.e., customers, permanent/temporary employees, consultants, and vendors). Free data from functional silos. Focus on identifying sources of unstructured data and real time data.
  2. Educate the Board and senior leaders about the need to invest in Artificial Intelligence to make sense of a digital data-rich world. If they do not appreciate the possibilities that digital tech can offer, they will not make the right investments. A digitally savvy board can be a great competitive advantage.
  3. Invest in cybersecurity talent. Build strict governance structures around data usage and privacy. The larger the data pond the more attractive it is to hackers.

Data is the new oil. Start running your organization with it.

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A slightly different version was written for DDI World <Read the original article>

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