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Agile Computing Authors: Pat Romanski, Brian Daleiden, Philippe Abdoulaye, Dana Gardner, Elizabeth White

Related Topics: @ThingsExpo, Java IoT, Mobile IoT, Linux Containers, @CloudExpo, @BigDataExpo

@ThingsExpo: Article

The Internet of Things, Code Halos and Enterprise Strategies | Part 1

Is data is the new competitive arena for businesses?

Tactics without strategy are dangerous. ~ Robert Leonhard

If you believe as the authors of the new book Code Halos do, that data is the new competitive arena for businesses, then you will want to develop a strategy in order to compete. What might that strategy look like? It may be as simple as, "We believe the better we understand the needs and preferences of our individual prospects and customers, the more convenient and personalized we can make their experiences which leads to happier and more loyal customers that promote our business and help us grow."

Streaming music stations provide us with a useful example of this kind of strategy. They enable me to personalize my music stations so I conveniently hear what I want, and as a result I listen to it more often. Amazon Prime knows my family intimately. They use this knowledge to enhance our shopping experience daily. Netflix knows our history and preferences and enhances our experience as a result.

Do you have a Code Halos strategy? Does your competition? Do the new digital start-ups in your industry?

Let's assume for today - you are convinced there is a need for a Code Halos strategy. Now let's consider tactics.

  1. What data would help you offer your prospects and customers an enhanced user experience on their smartphones or tablets?
  2. How can the data be used to enable a more personalized user experience?
  3. What is the best way to collect it?
  4. How do you ensure the data is collected in an honest and transparent manner with opt-in?
  5. How do you find business meaning in the data?
  6. How can new and different business meanings be discovered by aggregating seemingly unrelated data sources together?
  7. How can data from machines (M2M or the Internet of Things) add value to your other data sources?
  8. How can public and private databases be aggregated with "patterns of life" analysis and demographic data to discover new consumer insights?
  9. How can I collect data in real-time, analyze it and respond quick enough to be useful in a mobile first world?
  10. How can discovered real-time business meaning impact my real-time business tactics when interacting with prospects, customers, partners and employees?

These are just a few discussion starters for your next internal strategy session. By the way, we (Cognizant's Center for the Future of Work) lead these workshops all the time. Contact me if your organization would benefit from this discussion.

As identified earlier, one of the first questions to ask yourself is, "What data is useful?" What data, if you had it, would provide insight that would enable you to provide a better and more personalized user experience? If knowing your prospect is a male or female enables you to provide a better user experience, then how can you collect that data in an open, transparent and appropriate manner? Sometimes insight can be derived, while other times it just needs to be asked. If customer X shops only for fashionable clothes popular with young ladies, then there is a pretty good chance the buyer fits that description.

Did you know that mobile phone usage patterns differ between males and females? With a high degree of accuracy usage patterns can identify the sex of the user. Also, having preferences for particular kinds of music and artists closely correlates with particular political leanings. These are examples of derived insight.

Different data collection tactics provide different kinds of insights. Insights can be derived from historic data, or real-time GPS tracking for example. One is historic, the other is NOW! LBS (Location based services) and geo-fenced apps can trigger real-time product and services notifications, alerts, advertisements, discounts, etc., relevant to your immediate location.

Historic and real-time analysis may involve different systems, or the data can be combined in real-time to provide even greater business insights. For example, historic data might provide insight into a "pattern-of-life" that reflects a white collar business commuter, getting off of work at 5 PM every day, picking up the kids from daycare, collecting their dry cleaning, grocery shopping, filling up the Tahoe with gas every 10 days, and getting take-out Chinese food five days a week. Add in real-time LBS data and you can start looking for ways to add convenience and enhance this person's life through personalized products and services at just the right time and place.

Once you have identified the data you need to collect in order to derive business meaning, the next thing to consider is how that data can be used to personalize your user's experience. What does the collected data trigger that enhances the user's experience?

Stay tuned for Part 2.


Kevin Benedict
Writer, Speaker, Editor
Senior Analyst, Digital Transformation, EBA, Center for the Future of Work Cognizant
View my profile on LinkedIn
Learn about mobile strategies at
Follow me on Twitter @krbenedict
Browse the Mobile Solution Directory
Join the Linkedin Group Strategic Enterprise Mobility
Join the Google+ Community Mobile Enterprise Strategies
Recommended Strategy Book Code Halos
Recommended iPad App Code Halos for iPads

More Stories By Kevin Benedict

Kevin Benedict is the Senior Analyst for Digital Transformation at Cognizant, a writer, speaker and SAP Mentor Alumnus. Follow him on Twitter @krbenedict. He is a popular speaker around the world on the topic of digital transformation and enterprise mobility. He maintains a busy schedule researching, writing and speaking at events in North America, Asia and Europe. He has over 25 years of experience working in the enterprise IT solutions industry.

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