The New Mobile Shopper - Latest Research

I am deep into researching mobile consumer behaviors at this time, and am amazed at the impact that mobile technologies are having on us - especially millennials.

Here are some examples from my research:

  • People that use mobile devices to purchase products and services online, shop online far more frequently than those using only desktop/laptops.  In fact, mobile shoppers purchase online once or more a week at a rate 82% higher than desktop/laptop online shoppers.
  • People that use mobile devices to purchase products and services online, conduct research late at night, at a rate 46.1% higher than desktop/laptop online shoppers.
  • People that use mobile devices to purchase products and services online, check store inventories late at night at a rate 66.7% higher than desktop/laptop online shoppers. 
  • People that use mobile devices to purchase products and services online selected "ease of navigating the website or mobile app" as a top factor that influenced their decision to purchase online from a particular retailer/website at a rate 42.2% higher than desktop/laptop online shoppers. 
  • People that use mobile devices to purchase products and services online selected "the ability to buy/reserve online and pick-up in store" as a top factor that influenced their decision to purchase online from a particular retailer/website at a rate 53.4% greater than desktop/laptop online shoppers.
  • People that use mobile devices to purchase products and services online, report they have shopped for an item in a store, but purchased it online from a different retailer, at a rate 22% higher than desktop/laptop online shoppers.

  • This data came from Cognizant's 2015 Shoppers survey of 5,000 people.  It shows that people accustomed to using mobile devices to shop online for products and services represent a category of shopper that behaves very differently than traditional desktop/laptop online shoppers.  Retailers and etailers that don't account for these differences with customized/personalized digital experiences will lose to competitors that do.
    I will be finishing this research and publishing a major study on this data in the next few months.

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    Kevin Benedict
    Writer, Speaker, Senior Analyst
    Digital Transformation, EBA, Center for the Future of Work Cognizant
    View my profile on LinkedIn
    Read more at Future of Work
    Learn about mobile strategies at MobileEnterpriseStrategies.com
    Follow me on Twitter @krbenedict
    Subscribe to Kevin'sYouTube Channel
    Join the Linkedin Group Strategic Enterprise Mobility
    Join the Google+ Community Mobile Enterprise Strategies

    ***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.

    Mobile Consumer Behaviors - The Seven Essential Questions

    Digital Transformation is the process of updating your business and IT infrastructure to align with today's and tomorrow's consumers.  Today that is important, but hard to do.  Mobile consumer behaviors are changing far faster than most IT budgets and initiatives and that can cause problems.  If your customers are adopting technologies and changing their path-to-purchase journeys at a pace that is faster than you can deliver, then you are opening up an opportunity gap for a more nimble competitor.

    Do your internal sales and executive strategy sessions begin with these questions:
    1. Where are our customers to be found?  
    2. What technologies are our customers using?  
    3. How are our customers' path-to-purchase journeys' changing?  
    4. Are we meeting our customers along their path-to-purchase journeys and supporting them?
    5. Are we digitally transforming at a pace that will keep us aligned with our customers' pace of change?  
    6. Is our IT budget aligned with the required pace of change?  
    7. Are we re-engineering business processes to align with required digital transformations and mobile consumer behaviors?
    According to comScore's quarterly State Of Retail report, in the first quarter of 2014, 78 percent of the U.S. population age 15 and above bought something online.  That percentage is expected to continue to grow.  In addition, BusinessInsider.com reports the key age group of 18-34 year olds spend nearly $2,000 per year online now. In addition, in a recent Experian survey 55 percent of e-commerce shoppers in the U.S. live in households with incomes above $75,000 (40 percent were in households earning $100,000 and above). We are into serious numbers worthy of our attention.

    The point has been made.  We all recognize there is a lot of money to be made catering to online shoppers.  The problem is - just when many companies thought they had their e-commerce capabilities and strategies under control, consumer behaviors change.  How?  They jumped to mobile devices in the form of smartphones and tablets for much of the path-to-purchase journey.  In fact, in our analysis over three-quarters of path-to-purchase journeys are already completed before vendors are contacted, and much of it was completed using mobile devices.   If a retailer waits to be contacted before attempting to influence, they have missed the boat.  If marketing campaigns are desktop/laptop centric, they have missed key opportunities and demographics to influence.  If customers don't contact vendors until late in the path-to-purchase journey, then how can retailers effectively influence buying decisions?  They need to understand consumer behaviors in general, and mobile consumer behaviors in particular.

    In a recent survey I conducted of 108 business and IT professionals, all purchased products and services online.  Of those, eighty-nine percent purchase products and services online using mobile devices (smartphones and/or tablets).  However, when asked what means they typically use for online purchases, thirty-nine percent answered desktops/tablets, twelve percent mobile devices, and forty-eight percent answered both desktop/laptop and mobile devices regularly.  This data highlights the fact that many mobile consumers still wait to purchase products online using desktops/laptops even if they researched the products on smartphones and tablets.  The use of multiple devices and computers in the path-to-purchase process highlights the need to support customers across all channels to ensure they have a beautiful and consistent customer experience.   This is not easy as there are a lot of moving parts and technologies involved.

    To add to the complexity retailers face, different parts of the path-to-purchase journey are favored on different devices.  Yikes!  On-the-go searches and quick information discoveries are favored for smartphones.  Just search for a product or service and save the link.  In-depth research and rich product comparisons are often done on tablets with bigger screens.  For online purchases, consumers still overwhelmingly use desktops/laptops as they are assumed to be more secure.  Understood?  Don't, however, forget that many consumers still only use desktop/laptops and their behavior is different.  In fact, Cognizant just completed its 2015 Shoppers Survey of 5,000 people and forty-three percent typically only use computers for online shopping activities.

    How often do people use mobile devices to make online purchases?  From my recent survey (108 business and IT professionals):
    • Daily 1.8%
    • Weekly 28.7%
    • Monthly 43.5%
    • Quarterly 19.4%
    • Yearly 5.5%
    What time of day do consumers shop using mobile devices?  Here are the top three times from my recent survey ranked in order:
    1. Early morning
    2. Mid morning
    3. Early afternoon
    Seems simple. Focus from 6 AM to 2 PM in each time zone, right?  Wrong!  When you look at different mobile consumer behaviors by age, there are considerable differences.  That means if you are selling to an older age group, they have very different online and mobile consumer behaviors than 18-24 year olds. The younger age groups spike upward in online shopping late at night, after all of us old people are asleep in bed.  Besides, desktop users find shopping in bed quite painful after a few minutes.

    What location are mobile consumers at when they shop online?  That depends on what stage in the path-to-purchase they are in.  Here are the most popular locations for mobile consumer shopping from my recent survey ranked in order of popularity:
    1. Home - living room
    2. Work - desk
    3. Home - bedroom
    4. Home - TV room
    5. Coffee Shop/Restaurant
    6. Commuting - automobile/taxi/train/airplane/subway
    If this mix is not rich enough, let's add gender differences!  In a November 2014 study conducted by Burst Media and Rhythm NewMedia titled Online Insights - Mobile Shopping Behaviors, it was found that among respondents who use mobile device(s) inside a physical retail location to help with the shopping experience, 58.3 percent were women and 47.7 percent were men.  That difference is meaningful.

    I will stop here for today.  I am writing a lengthy report now on all the details of these studies.  If you would like to review these findings in detail and arrange a briefing, please contact me.  The bottom line is that consumers' path-to-purchase has been significantly impacted by mobile devices and if retailers and etailers are not in step with these changes, they will lose to competitors that are.

    ************************************************************************
    Kevin Benedict
    Writer, Speaker, Senior Analyst
    Digital Transformation, EBA, Center for the Future of Work Cognizant
    View my profile on LinkedIn
    Learn about mobile strategies at MobileEnterpriseStrategies.com
    Follow me on Twitter @krbenedict
    Subscribe to Kevin'sYouTube Channel
    Join the Linkedin Group Strategic Enterprise Mobility
    Join the Google+ Community Mobile Enterprise Strategies

    ***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.

    Interview: Robots, Digital Transformation and Intelligent Process Automation

    Robots bring to our minds images of dangerous humanoids, but business process robots look different and behave in very positive ways.  In this important conversation with three robot and automation experts, they reveal the presence of robots all around us, and their expanding roles in companies today.  Enjoy!

    Read the report - The Robot and I: How New Digital Technologies Are Making Smart People and Businesses Smarter. ************************************************************************
    Kevin Benedict
    Writer, Speaker, Senior Analyst
    Digital Transformation, EBA, Center for the Future of Work Cognizant
    View my profile on LinkedIn
    Learn about mobile strategies at MobileEnterpriseStrategies.com
    Follow me on Twitter @krbenedict
    Subscribe to Kevin'sYouTube Channel
    Join the Linkedin Group Strategic Enterprise Mobility
    Join the Google+ Community Mobile Enterprise Strategies

    ***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.

    Intelligent Mobile Commerce Apps, Digital Transformation, Robots and Speed

    Brains behind Mobile Applications
    In 2002, I was developing mobile applications for blue collar workers. These apps were not intelligent.  They were basically forms on handheld computers or PDAs.  Yes, they could be made to understand, based on data inputs, which form(s) should be presented next, but that was about as smart as they got.  In those days, mobile apps were mostly used to query a simple database and for field data collection and sync.

    Today, mobile apps on smartphones and tablets are the UXs (user interfaces) for very complex and intelligent systems, many of which today depend on software robots for automation and speed.  On a side note, yesterday, while I was attending a M6 Mobility Xchange conference, Intel said us humans are becoming part of the computer!

    Mobile users are impatient.  They will wait less than 4 seconds on average for a mobile app to load, before closing it and moving on. You would hate to have developed the world's best designed mobile application, but then have mobile consumers abandon it, because some transaction engine, integrated product catalog or mobile security system made the process too slow.

    Let me provide a scenario - a person uses a retailer's mobile application that is associated with a loyalty program.  The millisecond they load the application, software robots on the backend identify the device, look at all the accumulated data about the user's transaction histories, demographics, preferences, styles, etc., analyzes it, and then create a personalized experience which is uploaded to the mobile application.  No human is involved, but the experience is fast, beautiful and personal.  The products and discounts are optimized to appeal to my preferences.  It is an automated process that uses software robots to analyze and act in milliseconds.  This process is far more sophisticated and complex than the processes I used in 2002.

    In 2002, to speed up a process we looked at just a few areas: the selected mobile device, wireless networks, device memory and the size of the database queries.  Today, entire business processes are being impacted and companies are being forced to rethink operations.  Legacy IT systems are being asked to perform at speeds beyond their capabilities.  Mobile solutions today, are more about the backend servers, processes, robots and strategies, than the actual mobile app.

    The pressure to digitally transform and automate IT environments is growing.  Mobile applications, at first just clever add-ons to line of business applications, are now driving the train of digital transformation and pointing the way to the future for the entire enterprise.  The cost of a mobile application, may ultimately involve rethinking your entire IT environment.

    As consumers increasingly shop online and mobile, competition will force businesses to redesign not only their IT environments, but their entire approach to marketing, sales, customer service and R&D as well.

    Finally a big favor to ask - Will you take my 3-minute survey on mobile behaviors?  It is part of an in-depth mobile consumer behaviors and the retail experience report I am working on.

    Survey - http://survey.constantcontact.com/survey/a07eb005ar4i9lm8rvk/start
    ************************************************************************
    Kevin Benedict
    Writer, Speaker, Senior Analyst
    Digital Transformation, EBA, Center for the Future of Work Cognizant
    View my profile on LinkedIn
    Learn about mobile strategies at MobileEnterpriseStrategies.com
    Follow me on Twitter @krbenedict
    Subscribe to Kevin'sYouTube Channel
    Join the Linkedin Group Strategic Enterprise Mobility
    Join the Google+ Community Mobile Enterprise Strategies

    ***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.

    The Latest Trends in Mobile Commerce that You Can't Miss

    In a recent survey, conducted by Cognizant's Center for the Future of Work and Cognizant's retail practice, we found that of 5,000 people who make online purchases at least a few times each year, 68.1% (3,918) make online purchases at least once a month.  Out of this group, here are the age breakdowns:
    • 71.6% of 18-24 year olds make online purchases at least once a month, and 77.3% of these report using mobile devices at least as much as desktop/laptops for online purchases.
    • 79.8% of 25-34 year olds make online purchases at least once a month, and 82.2% of these report using mobile devices at least as much as desktop/laptops for online purchases.
    • 74.1% of 35-44 year olds make online purchases at least once a month, and 79.9% of these report using mobile devices at least as much as desktop/laptops for online purchases.
    • 69.7% of 45-54 year olds make online purchases at least once a month, and 75.7% of these report using mobile devices at least as much as desktop/laptops for online purchases.
    • 61.6% of 55-64 year olds make online purchases at least once a month, and 68.2% of these report using mobile devices at least as much as desktop/laptops for online purchases.
    • 55.2% of 65+ year olds make online purchases at least once a month, and 61.8% of these report using mobile devices at least as much as desktop/laptops for online purchases.
    These are interesting numbers, but not necessarily unexpected.  The biggest discoveries in the data are found in the behavioral differences of mobile consumers.  E-Commerce or website based online commerce has been around for over 15 years, and most retail companies have been interacting with their markets via websites long enough to have a solid understanding of online behaviors, but mobile commerce is still new and dynamic enough that uncertainties remain.

    Here are a few interesting findings I discovered while researching for my latest report on Mobile Consumer Behaviors and the Retail Experience.
    • 24% of 5,000 survey participants, report they research and/or compare prices using a mobile device while shopping in-store most of the time to every time - 44% rarely to never do.
    • Survey participants that use mobile devices at least equal to desktops/laptops, shop online once or more a week at a rate 82% higher than desktop/laptop users.
    • Mobile shoppers conduct research late at night at a rate 46.1% higher than desktop/laptop online shoppers.  That makes sense, desktops are kind of heavy to take with you to bed.
    After my first couple of passes through this new data, it is obvious there are significant behavioral differences between mobile shoppers, desktop/laptop shoppers and offline shoppers.  These behavioral differences, given the rapid growth of mobile commerce, must be understood and integrated into sales and marketing systems and strategies in order to maximize success.

    If your company is involved in retail and mobile commerce and would like to meet and review all of my latest findings, please contact me here.

    ************************************************************************
    Kevin Benedict
    Writer, Speaker, Senior Analyst
    Digital Transformation, EBA, Center for the Future of Work Cognizant
    View my profile on LinkedIn
    Learn about mobile strategies at MobileEnterpriseStrategies.com
    Follow me on Twitter @krbenedict
    Subscribe to Kevin'sYouTube Channel
    Join the Linkedin Group Strategic Enterprise Mobility
    Join the Google+ Community Mobile Enterprise Strategies

    ***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.

    Mobile Apps - Personalizing While Respecting Personal Privacy

    All the data I have been reading this week suggest mobile users want and value a personalized experience on their mobile apps or mobile website, but on the other hand they don't like giving up their personal data.  That means it is imperative to find the right balance so a mutually satisfying relationship can be fostered.  As we all know, the more data you have on an individual, the easier it is to configure a personalized experience.

    In a fresh Cognizant survey this week involving 5,000 participants, 68% reported they are willing to provide information on their gender, 55% their age, and 65% their brand and product preferences, but the majority are not in favor of volunteering much else.  That is an interesting answer since 80% of the same survey participants belong to one or more loyalty and rewards programs, and the biggest reasons according to 74% are the points or rewards for each dollar spent.  The second biggest motivation was automatic discounts for loyalty program members.  That tells us there is a willingness to give up some level of data privacy if the rewards and discounts are valuable enough.

    Mobile retailers need to find out how much personal data is worth to their customer base.  They need to give up enough in points, rewards and discounts to motivate the sharing of more in depth personal data.  Collecting data on social media is not the answer.  In my research, consumers don't like the idea of any kind of data collection for marketing purposes from their social media activities.  It makes them mad.  Mad is not a feeling a consumer products company wants to elicit from their customers.

    It seems to me that a bold, transparent process would be best.  The online and mobile retailer should place a value on data.  For example:
    • Answer 10 specific questions about yourself and your preferences, and I will give you an automatic 10% off your purchases.
    • Answer 20 specific questions about yourself and your preferences, and I will give you an automatic 20% off your purchases.
    • Answer 30 specific questions about yourself and your preferences, and I will give you an automatic 30% off your purchases.
    Whatever the real value, we all agree that there is a value to data.  Finding the real value, and transparently using that information to provide a personalized user experience, benefits all parties.

    I think IoT (Internet of Things) sensors may also play a role in data collection and personalization. Rather than make people uncomfortable by tracking more personal data, sensors can track product data and that can be used to provide a personalized experience for the owner of the product.  Here is an example - a man buys a bass fishing boat and a service agreement.  Sensors (as defined in the service agreement) collects data on the boat engine.  Information such as:
    • Locations
    • Activities
    • Usage profiles
    • Hours of operations
    • Data and time
    • etc.
    The boat engine information is added to the customer's profile to provide a "boater's profile" that can be used to personalize online and mobile experiences.

    Follow me on Twitter @krbenedict.
    ************************************************************************
    Kevin Benedict
    Writer, Speaker, Senior Analyst
    Digital Transformation, EBA, Center for the Future of Work Cognizant
    View my profile on LinkedIn
    Learn about mobile strategies at MobileEnterpriseStrategies.com
    Follow me on Twitter @krbenedict
    Subscribe to Kevin'sYouTube Channel
    Join the Linkedin Group Strategic Enterprise Mobility
    Join the Google+ Community Mobile Enterprise Strategies

    ***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.

    Speed, Personalization, Analytics and Enterprise Information Systems

    Ninety percent of 18-34 years old strongly value a personalized mobile and web experience, and eighty-two percent of of those over 45 years old value personalization.  What kind of personalization?  Forty-seven percent of shoppers prefer location or time-based personalization in mobile applications or websites.  In other words, don't show me things that are not available for me to purchase in Boise at this time, or that I don't like!  Given this survey data we all know what needs to be done and are taking the necessary steps to be able to offer personalization, right?  Wrong it seems.  Many companies are not using available data to understand their customers better so they can provide them with contextually relevant and personalized mobile application experiences.

    My colleague, Benjamin Pring, at Cognizant's Center for the Future of Work recently published a research paper titled Putting the Experience in Digital Customer Experience.  In his research he found fewer than 20% of respondents use analytics generated by application programming interface (API) traffic to understand their customers’ online and offline purchase journeys.  Just 41% of respondents in the retail industry say they will be effective at analyzing customer metadata by 2017.  A mere 42% of respondents say they have adequate tools and skills to analyze digitally generated data.  Only one-third of respondents have made adjustments to their business model to pursue strategies driven by digital information about their customers.

    An additional challenge, is that personalizing mobile user experiences takes speed, speed many do not have available in their current IT environments.  As organizations begin developing mobile strategies and implementing mobile apps, they quickly realize simply developing and deploying basic mobile apps, infrastructure and frameworks is not enough.  They must push further and implement a real-time enterprise to remain competitive.  This real-time requirement is at the root of many problems.  Eighty-four percent of survey participants reported they have IT systems too slow or incapable of supporting real-time mobility, which negatively impacts mobile app performance and the user’s experience.

    We have some more work to do.


    ************************************************************************
    Kevin Benedict
    Writer, Speaker, Senior Analyst
    Digital Transformation, EBA, Center for the Future of Work Cognizant
    View my profile on LinkedIn
    Learn about mobile strategies at MobileEnterpriseStrategies.com
    Follow me on Twitter @krbenedict
    Subscribe to Kevin'sYouTube Channel
    Join the Linkedin Group Strategic Enterprise Mobility
    Join the Google+ Community Mobile Enterprise Strategies

    ***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.

    Monitoring an Ear of Corn with an IoT Sensor?

    Once upon a time, farmers would walk through a field or ride a horse around it to determine the amount of fertilizer and water their crops required.  I have done this myself.  Today agricultural drones with sensors and analysis software can fly over large fields and analyze the crops and their needs precisely in seconds.  If we wanted to get even more ambitious, we could place an IoT (Internet of Things) sensor next to every stalk of corn to monitor and optimize its growth.  Although these steps are all feasible today, some are not yet economically advantageous.  That might, however, soon change.  In the past, we treated crops in aggregate. Today, we can customize how we treat each section of a crop due to the benefits of sensors.

    Globally, we will need to feed 8 billion people by 2030 and 9 billion by 2050.  The UN Food and Agriculture Organization (FAO) projects that, under current production and consumption trends, global food production must increase 60 percent by 2050 in order to meet the demands of the growing world population.  That's only 35 years away!!!

    Another fact, over 25-40% of our food spoils or is lost before it can be consumed (source http://www.foodwastealliance.org/about-our-work/assessment/).  This is a massive amount of waste and inefficiency that no one wants and IoT sensors can help us reduce food waste.

    Do you see, as I do, the need for a digital transformation in agriculture, food processing and delivery? The Internet of Things is not just the newest gadget for us to play with, it can mean the difference between life and death for many people.  Data collected through sensors and analyzed to help optimize growth, harvesting, processing, delivery and consumption may just be the solution we need.



    ************************************************************************
    Kevin Benedict
    Writer, Speaker, Senior Analyst
    Digital Transformation, EBA, Center for the Future of Work Cognizant
    View my profile on LinkedIn
    Learn about mobile strategies at MobileEnterpriseStrategies.com
    Follow me on Twitter @krbenedict
    Subscribe to Kevin'sYouTube Channel
    Join the Linkedin Group Strategic Enterprise Mobility
    Join the Google+ Community Mobile Enterprise Strategies

    ***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.

    Top 11 Articles on IoT, Mobility, Code Halos and Digital Transformation Strategies

    Most of the stuff I write is rubbish, but these 11 articles beat the odds and are actually worth reading. You can find my complete Top 40 list here. Enjoy!

    1. Mobile Apps, Blind Spots, Tomatoes and IoT Sensors
    2. IoT Sensors, Nerves for Robots and the Industrial Internet
    3. Sensors - Sensing and Sharing the Physical World
    4. IoT Sensors, Tactile Feedback, iPhones and Digital Transformation
    5. IoT, Software Robots, Mobile Apps and Network Centric Operations
    6. Networked Field Services and Real-Time Decision Making
    7. Thinking About Enterprise Mobility, Digital Transformation and Doctrine
    8. GEOINT, GIS, Google Field Trip and Digital Transformation
    9. Connecting the Dots Between Enterprise Mobility and IoT
    10. Merging the Physical with the Digital for Optimized Productivity
    11. IoT Sensors Extend Our Physical Senses Beyond Our Physical Reach
    You can find my Top 75 articles on Mobile Strategies here.

    ************************************************************************
    Kevin Benedict
    Writer, Speaker, Senior Analyst
    Digital Transformation, EBA, Center for the Future of Work Cognizant
    View my profile on LinkedIn
    Learn about mobile strategies at MobileEnterpriseStrategies.com
    Follow me on Twitter @krbenedict
    Subscribe to Kevin'sYouTube Channel
    Join the Linkedin Group Strategic Enterprise Mobility
    Join the Google+ Community Mobile Enterprise Strategies

    ***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.

    IoT Sensors, Nerves for Robots and the Industrial Internet

    Sensors are Nerves for Robots
    Yesterday I interviewed two robotics experts on the growing demand for IPAs (intelligent process automation) robots.  These robots are made of software code.  They are assigned pre-defined actions based on steps in a process, the analysis of data, and the decision trees they are provided.  For example, an IPA can review a car loan application and approve or disprove it instantly – based on the data.  In fact, they can analyze the data from tens of thousands of car loans in seconds based on the parameters and decision trees they have been given.

    There are literally hundreds of thousands of different use cases for IPA robots.  IPA robots can also interact with IoT sensors and take actions based on sensor data.  Not just by completing a digital business processes, but even by controlling physical equipment and machines as well.  Sensors serve robots in much the same way as nerves serve us humans.

    Earlier this week I was briefed by a company AMS AG,  a developer of IoT sensors.  They just released a new sensor that smells odors in homes and offices.  Yes, indeed!  The sensor is embedded in a home monitoring system from Withings.  In Withings’ Home product, the AS-MLV-P2 (sensor) is combined with a 5Mpixel video camera, dual microphones, temperature and humidity sensors and Wi-Fi® and Bluetooth® Smart radios. This means that users of the Home monitoring system can see, hear, feel and smell the inside of their home or office remotely via a smartphone or tablet app supplied by Withings.

    AMS’s sensor detects VOCs (volatile organic compounds), including both human-made and naturally occurring chemical compounds. These include ambient concentrations of a broad range of reducing gases associated with bad air quality such as alcohols, aldehydes, ketones, organic acids, amines, and aliphatic and aromatic hydrocarbons, all which can be harmful to human and animal health at high levels. These are most of the scents humans smell.  In the Home app, the sensor’s measurements of these chemicals are converted to an air-quality rating as well as to a measurement of VOC concentrations.

    If you combine IPA robots, AMS’s sensors and Withings Home monitoring system with your HVAC system, the IPA robot can ensure you have healthy air quality in your home or office continuously. In fact, an IPA robot could manage the air quality and security of tens of thousands of homes and offices at the same time.  The results of these findings and actions can be displayed and controlled on smartphones and tablets as well.

    Not only do you have robots sensing the physical world, but also automatically reacting to it on your behalf.  In my opinion, how sensors detect and communicate the physical and natural world to humans and robots is one of the most interesting areas of innovation today.

    An additional value of using IPA robots is the massive clouds of data they spin-off as a result of their decisions and actions.  This data can be further analyzed to find new areas for optimization and potential business opportunities.  Herein lies an emerging area where big data analysis can give us even deeper insights.



    ************************************************************************
    Kevin Benedict
    Writer, Speaker, Senior Analyst
    Digital Transformation, EBA, Center for the Future of Work Cognizant
    View my profile on LinkedIn
    Learn about mobile strategies at MobileEnterpriseStrategies.com
    Follow me on Twitter @krbenedict
    Subscribe to Kevin'sYouTube Channel
    Join the Linkedin Group Strategic Enterprise Mobility
    Join the Google+ Community Mobile Enterprise Strategies

    ***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.

    Robots and I - Intelligent Process Automation, Siri and More

    Today I had the privilege of interviewing two robotics and process automation experts.  I learned there are many different kinds of robots including the humanoid types we see in movies, and robots made entirely out of software.  In this interview we discuss Rob Brown's recent white paper titled Robots and I, the different forms of robots, and then dig deep into how software robots are transforming many industries today with expert Matt Smith.  Enjoy!

    Video Link: https://youtu.be/qOPFD3vshec


    ************************************************************************
    Kevin Benedict
    Writer, Speaker, Senior Analyst
    Digital Transformation, EBA, Center for the Future of Work Cognizant
    View my profile on LinkedIn
    Learn about mobile strategies at MobileEnterpriseStrategies.com
    Follow me on Twitter @krbenedict
    Subscribe to Kevin'sYouTube Channel
    Join the Linkedin Group Strategic Enterprise Mobility
    Join the Google+ Community Mobile Enterprise Strategies

    ***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.

    Mobile Apps, Blind Spots, Tomatoes and IoT Sensors

    Master Tomato Gardener
    A lot is written on mobile technologies, the Internet of Things, social media and analytics, but little is written on how all these might work together in a retail environment.  I think best by writing, so let's think this through together.

    Blind spots are defined as, “Areas where a person's view is obstructed.” Many business decisions today are still made based on conjecture (unsubstantiated assumptions), because the data needed to make a data-driven decision lies in an operational “blind spot.”

    Smart companies when designing mobile applications consider how they can personalize the user experience.  They ask themselves how they can utilize all the accumulated data they have collected on their customers or prospects, plus third-party data sources, to make the experience as beautiful and pleasurable as possible.  To start, they can often access the following kinds of data from their own and/or purchased databases to personalize the experience:
    • Name
    • Age
    • Gender
    • Address
    • Demographic data
    • Income estimate
    • Credit history
    • Education level
    • Marital status
    • Children
    • Lifestyle
    • Social media profile and sentiment
    • Job title
    • Purchase history
    • Locations of purchases
    • Preferences, tastes and style
    • Browsing/Shopping history
    This data, however, is basic.  It is merely a digital profile. It has many blind spots.  It is often not based on real-time data.  As competition stiffens, the above profile data will not be enough to deliver a competitive advantage.  Companies will need to find ways to reduce blind spots in their data so they can increase the degree of personalization.

    Sensors connected to the IoT (Internet of Things) will play an important role in reducing blind spots. Sensors, often cost only a few dollars, and can be set-up to detect or measure physical properties, and then wirelessly communicate the results to a designated server.  Also as smartphones (aka sensor platforms) increase the number of sensors they include, and then make these sensors available to mobile application developers through APIs, the competitive playing field will shift to how these sensors can be used to increase the level of personalization.

    Let’s imagine a garden supply company, GardenHelpers, developing a mobile application.  The goal of the application is to provide competitive differentiation in the market by offering personalized garden advice and solutions.  The GardenHelpers use the following smartphone sensors in their design to provide more personalized gardening advice:
    • GPS sensor (location data)
    • Cell Tower signal strength (location data)
    • Magnetometer sensor (location of sun)
    • Ambient light sensor (available sunlight)
    • Barometer sensor (altitude)
    GardenHelpers combine the sensor data with date and time, plus third-party information such as:
    • GIS (geospatial information system on terrain, slopes, angles, watershed, etc.) data
    • Historic weather information
    • Government soil quality information
    • Government crop data, recommendations and advice
    GardenHelpers also encourages the user to capture the GPS coordinates, via their smartphone, on each corner of their garden to input the estimated garden size, and to capture the amount of sunlight at various times of the day through the ambient light sensor.  This information is compared with area weather data and the amount of shade and sunlight on their garden is estimated.

    GardenHelpers now understands a great deal about the gardener (mobile app user), the garden location, size, lay of the land and sunlight at various times.  However, there remain “blind spots.”  GardenHelpers doesn't know the exact temperature, wind speeds, humidity levels, or the amount of water in the soil of the garden.  How do they remedy these blind spots?  They offer to sell the gardeners a kit of wireless IoT sensors to measure these.

    With all of this information now the blind spots are now greatly reduced, but some remain.  What about local pests, soil issues and advice?  GardenHelpers adds a social and analytics element to their solution.  This enables gardeners to share advice with other local gardeners with similar garden sizes and crops.

    GardenHelpers can now deliver a mobile app that is hyper-personalized for their customers and prospects.  The products they offer and recommend are not selected randomly, but are now based on precise smartphone and sensor data. The mobile app combined with the IoT sensors become an indispensable tool for their customers which leads to increased brand loyalty and sales.

    ************************************************************************
    Kevin Benedict
    Writer, Speaker, Senior Analyst
    Digital Transformation, EBA, Center for the Future of Work Cognizant
    View my profile on LinkedIn
    Learn about mobile strategies at MobileEnterpriseStrategies.com
    Follow me on Twitter @krbenedict
    Subscribe to Kevin'sYouTube Channel
    Join the Linkedin Group Strategic Enterprise Mobility
    Join the Google+ Community Mobile Enterprise Strategies

    ***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.

    Sensors - Sensing and Sharing the Physical World

    Global Sensor Data
    We spend a lot of time talking and writing about the IoT (Internet of Things) in the macro, as a giant worldwide network of objects and things, communicating with themselves and others.  That is indeed interesting, but the most interesting components of the IoT, in my opinion, are the sensors.  Sensors are defined as, "Devices that detect or measure a physical property and record, indicate, or otherwise responds to it."  In the context of IoT, sensors detect or measure a physical property and then communicate the findings wirelessly to a server for analysis. Sensors are our digital fingers that touch and feel the earth and environment!

    Just last week I read this about a new iPhone patent, "The patent is titled “Digital camera with light splitter.” The camera described in the patent has three sensors for splitting color. The camera would split colors into three different rays. These would be red, green and blue. The splitting of colors is designed to allow the camera to maximize pixel array resolution." This patent potentially could help Apple improve the image quality of its mobile cameras, especially in video.  In other words, it will help iPhones better capture, display and share the scenes on our planet for viewing.

    At the Mobile World Congress in Barcelona this year I saw demonstrated an iPhone add-on from the company, Flir.   It was a Personal Thermal Imagery Camera.  You connect it to your iPhone and then you can find leaky pipes in your wall, overloaded electrical breakers, or even spot live rodents hiding in your walls. You can use it in your boat to spot floating debris in the water in the dark or use while hiking in the dark to spot hidden predators preparing to devour you.  I WANT ONE NOW!

    Sensors measure and collect data and can be connected to just about any piece of equipment. Satellite cameras are sensors.  There are audio and visual sensors.  There are pressure and heat sensors.  There are all kinds of sensors.  One of the most interesting sensor technologies I have been researching of late is hyper spectral remote sensors.

    Hyper spectral sensors combined with GIS (geospatial information systems) information and Big Data analytics are a powerful mix. These sensors can be integrated into very powerful cameras. Hyper spectral remote sensing is an emerging technology that is being studied for its ability to detect and identify minerals, terrestrial vegetation, and man-made materials and backgrounds.  I want one!

    Hyper spectral remote sensing combines imaging and spectroscopy (spectroscopy is a term used to refer to the measurement of radiation intensity as a function of wavelength) in a single system, which often includes large data sets that require Big Data analytics.  Hyper spectral imagery is typically collected (and represented) as a data cube with spatial information collected in the X-Y plane, and spectral information represented in the Z-direction.
    hyper spectal imaging

    What can be done with hyper spectral remote sensing?  Using powerful hyper spectral cameras one can detect unique noble gases (each unique gas emits a unique color on the spectrum), different inks, dyes and paints (each have different characteristics that can be uniquely identified).  You can detect, identify and quantify chemicals.  You can detect chemical composition and physical properties including their temperature and velocity all with a camera!

    Taking a hyper spectral image of an object, connected to real-time Big Data analytics, can tell you an amazing amount of information about it.  Theoretically, a hyper spectral image of a person combined with facial recognition can identify a person, their shampoo, make-up, hand lotion, deodorant, perfume, the food they ate, chemicals they have been in contact with and the materials and chemicals used in their clothes.  OK, the implications of this technology for personal privacy are really creepy, but the technology itself is fascinating.

    Theoretically hyper spectral remote sensing systems can be used for healthcare, food monitoring, security at airports, for public safety, in intelligence systems and integrated with drone and satellite surveillance systems.

    Today, luckily, these cameras are far too expensive for me.

    Related Articles: http://mobileenterprisestrategies.blogspot.com/2015/04/iot-sensors-tactile-feedback-iphones.html

    Related Video: http://mobileenterprisestrategies.blogspot.com/2015/03/iot-and-sensors-from-ams-at-mwc15.html
    ************************************************************************
    Kevin Benedict
    Writer, Speaker, Senior Analyst
    Digital Transformation, EBA, Center for the Future of Work Cognizant
    View my profile on LinkedIn
    Learn about mobile strategies at MobileEnterpriseStrategies.com
    Follow me on Twitter @krbenedict
    Subscribe to Kevin'sYouTube Channel
    Join the Linkedin Group Strategic Enterprise Mobility
    Join the Google+ Community Mobile Enterprise Strategies

    ***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.

    IoT Sensors, Tactile Feedback, iPhones and Digital Transformation

    IoT sensors extend our physical senses beyond our physical reach and communicate the results from afar. They also allow us to share experiences remotely, not just mentally, but also tactilely. That is the first time I have ever used the word “tactilely.” It means to tangibly or physically experience something. For example, AMS’s MEMS gas sensor allows people to hear, see and smell inside their home remotely from an iPhone app. The Withings Home camera sends alerts to an iPhone if it detects movement or noise in the house. Its night-vision sensor mode enables the remote viewer to even see in the dark. The viewer can also talk through the camera to ask questions like, “Who are you, and why are you carrying my big screen TV away?”

    Today you can combine 3D modeling apps for smartphones and tablets with sounds, vibrations and colors so you can augment your reality with tactile experiences. Wireless sensors and 3D modeling and visualization tools enable you to see and monitor conditions at distance - in real-time. A combination of sensors, analytics, visualization and tactile feedback tools can alert and inform you of changing conditions, patterns or variations in activity or data patterns. This experience can truly augment your reality.

    The new Apple Watch enables you to signal somebody on the other side of the world with tactile vibrations that you customize. For example, while on the road I can signal my wife that I miss her by sending five quick “pulses” that vibrate on her wrist.

    Digitally modeled realities enable experts, from anywhere in the world, to work and manage factories, farms and other kinds of operations from distant locations. The obstacles of the past, lack of information and monitoring capabilities, that resulted in operational blind spots are quickly disappearing as more sensors are put in place. Most of us either own or have seen noise canceling headsets. Sensors in the headset capture the incoming noise and then instantly counter with anti-sound that matches the sensor data. This same kind of sensor technology can capture noise and transmit it to distant locations where it can be recreated and listened to by others.

    I can image near-term scenarios where entire factory floors are digitally replicated and real-time operations can be viewed and managed from great distances. Every component of the operation can be monitored via sensor data. Aberrations, out of compliance data, and other faults would instantly cause alerts, notifications and remedies to be implemented.

    In the military arena, acoustical sensors can now pin-point the location of incoming bullets, rockets, missiles, etc., in real-time and activate various instantaneous counter measure technologies. Data means power.

    Today's competitive marketplace requires companies to collect more data, analyze more data and utilize more data to improve customer interactions and engagements. Mobile devices are exceptionally designed to assist in this effort. Apple's iPhone and Apple Watch come with an array of sensors for collecting data about your surroundings:
    • Touch/Multi-Touch screen sensor
    • Force Touch sensor– measures different levels of touch (Apple Watch), determines the difference between a tap and a press
    • Taptic Engine sensor – tactile feedback via gentle vibration(Apple Watch)
    • Audio/Voice sensor
    • GPS sensor
    • Bluetooth sensor (supports iBeacon)
    • WiFi sensor
    • WiFi strength sensor – help track indoor activities
    • Proximity sensor - deactivates the display and touchscreen when the device is brought near the face during a call, and it shuts off the screen and touch sensitivity
    • Ambient Light sensor - brightens the display when you’re in sunlight and dims it in darker place
    • Magnetometer sensor - measure the strength and/or direction of the magnetic field in the vicinity of the device – runs digital compass
    • Accelerometer sensor- measures the force of acceleration, i.e. the speed of movement (uses movement and gravity sensing), steps counter, distance, speed of movement, detects the angle an iPhone is being held
    • Apple Watch sensors measure steps taken, calories burned, and pulse rate
    • Gyroscope – 3 axis gyro (combined with Accelerometer provides 6 axis motion sensing), Pitch, Roll and Yaw
    • Barometer sensor – altitude, elevation gain during workouts, weather condition
    • Camera sensor with a plethora of sensors and digital features: face detection, noise reduction, optical image stabilization, auto-focus, color sensors, backside Illumination sensor, True Tone sensor and flash 
    • Fingerprint identity sensor
    • Heart rate sensor (Apple Watch) - uses infrared and visible-light LEDs and photodiodes to detect heart rate Sensor
    Other sensor add-ons: Personal Thermal Imagery Cameras sensor (Flir)

    I attended a defense related conference and listened to an IT expert in the CIA present on how they can use sensors on smartphones to uniquely identify the walking style and pace of individuals. For example, the intelligence agency may suspect a person carrying a phone is a bad guy. They can remotely switch on the smartphone's sensors and record the walking style and pace of the person carrying the phone and match it with their database records.

    Sensors help bridge the gap between the physical and digital worlds. They convert the physical world into data. Tactile feedback tools convert the data back into physical experiences – like a Star Trek Transporter.

    Mobile apps can also be considered the API (application programming interface) between humans and smartphones. Sensors are the API between the phone and the physical world. For example, a mobile application for recommending local restaurants may start by asking the user what kind of food they prefer. The human queries their stomach for pain and preferences, and then inputs the results into mobile apps by touching the keypad or using their voice. Suddenly a server in an Amazon data center knows your stomach's inputs! That is one powerful sensor and API! Given the vast array of sensors in the human body incredible things can be done once those sensor convert them to data.

    Until recently, the data from natural sensors in the human body were mostly communicated to analytics engines via human's touch, typing, drawings or voice inputs. The emergence of wearable sensors and smart devices, however, change that. Wearable sensors can bypass the human in the middle and wirelessly communicate directly with your applications or healthcare provider.

    Sensors and computers are also connected to the non-physical. Applications can react differently based on recognized time inputs. Once time reaches a specified location (place?), an alarm can be activated sending sound waves to your physical ear. That is converting the non-physical (time) into sound waves that vibrate our ear drums.

    The challenge for businesses today is to envision how all of these sensors and available real-time data can be used to improve sales, customer service, product design, marketplace interactions and engagements so there are more profits at the end of the day.

    In the book Digital Disruptions, James McQuivey writes that for most of history, disruptions (business and marketplace transformations) occurred in a physical world of factories and well-trod distribution networks. However, the disruptors of tomorrow are likely coming from digital disruptions - sensors, code halos, big data, mobile devices and wearables.

    The task and challenge of every IT department is to understand and design a strategy that recognizes the competitive playing fields of tomorrow are among the digits.


    ************************************************************************
    Kevin Benedict
    Writer, Speaker, Senior Analyst
    Digital Transformation, EBA, Center for the Future of Work Cognizant
    View my profile on LinkedIn
    Learn about mobile strategies at MobileEnterpriseStrategies.com
    Follow me on Twitter @krbenedict
    Subscribe to Kevin'sYouTube Channel
    Join the Linkedin Group Strategic Enterprise Mobility
    Join the Google+ Community Mobile Enterprise Strategies

    ***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.

    Mobile Apps, Analytics, Code Halos and Mass Personalization

    Kevin Benedict, moderates this panel of digital experience and mobility experts including Benjamin Pring, Ted Shelton and Jack C. Crawford as they review and discuss the findings of Ben Pring's recent study Putting the Experience in Digital Customer Experience.

    Video Link: https://youtu.be/xsPDWReccF4?list=UUGizQCw2Zbs3eTLwp7icoqw

    ************************************************************************
    Kevin Benedict
    Writer, Speaker, Senior Analyst
    Digital Transformation, EBA, Center for the Future of Work Cognizant
    View my profile on LinkedIn
    Learn about mobile strategies at MobileEnterpriseStrategies.com
    Follow me on Twitter @krbenedict
    Subscribe to Kevin'sYouTube Channel
    Join the Linkedin Group Strategic Enterprise Mobility
    Join the Google+ Community Mobile Enterprise Strategies

    ***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.

    IoT, Software Robots, Mobile Apps and Network Centric Operations

    Articles about the IoT (Internet of Things) have moved from technical journals to our daily newspapers.  In this article we will go beyond the simplistic applications talked about in the local paper and discuss how IoT and complementary technologies, including software robots, can add real business value to the rugged outdoor work found in many industries.

    In the rugged blue collar environment, vehicles, high valued equipment and other assets can be connected to the IoT to wirelessly report on their status, hours of operation, location, environment, maintenance and repair needs. This data can alert management when there is a problem, event or automatically create service tickets or send alerts when an action or decision is required. The IoT has the ability to provide "situational awareness" across large geographic areas and thousands of assets all at the same time.  This capability helps both decision-makers and automated systems (software robots) better understand how to optimize the use of experts, equipment and schedules across different geographic areas.

    Today, sensors can be connected to many different pieces of equipment and are capable of bidirectional data exchanges.  That means they can both send data and receive data.  Data sent to them can include commands to perform a task.  These tasks may be to unlock a door, open a gate, increase or decrease the temperature, reposition a video camera, or to remotely operate equipment, think drones!  This capability is powerful and we are just scratching the surface of possibilities.

    The IoT delivers on a vision of connecting physical and digital items to each other wirelessly through a network. These connections, and the data exchanged, can provide real-time access to information about the physical world in distant and remote locations.  This information can be analyzed by humans or software robots and turned into actionable intelligence that can be utilized by automated systems or human decision-makers. Connected IoT devices integrated into business systems can lead to many innovation and gains in efficiency and productivity that were never before possible.

    A few of the key markets for IoT are:
    • Utilities/Smart grids
    • Defense
    • Fleet management/Automotive systems
    • Field services management
    • Rental equipment
    • Heavy equipment monitoring (think tractors, bulldozers, cranes, etc.)
    • Plant maintenance
    • Facility management
    • Connected homes/Home Energy Management Systems (HEMS)
    • Healthcare - fitness, remote patient and health monitoring
    • Medical equipment monitoring
    • Vending machines
    • ATMs
    • POS systems
    • Remote asset management monitoring
    • Security systems
    • Consumer electronics (eReaders, Wireless Printers, Appliances, etc.) 
    • etc.
    In a world filled with data from mobile users, databases, websites and the IoT, the big question is what can be done with all of this data? This is where real-time analytics are required - analytic solutions that have the capacity and capability to analyze large amounts of incoming data in real-time.  The results of their analysis can be utilized by humans and/or software robots to optimize productivity and efficiencies.  Many of today's most advanced workforce optimization and scheduling solutions use software robots that can instantly react to the real-time data and optimize thousands of schedules and assignments in seconds (see ClickSoftware).

    What are software robots?  According to a new study by my colleague, Rob Brown, at the Center for the Future of Work, titled The Robot and I, humans are working smarter with sophisticated software (robots) to automate business tasks that help humans attain new levels of process efficiency, such as improved operational costs, speed, accuracy and throughput volume.  In short, software robots are digital assistants and force-multipliers for humans.

    Data and Real-Time Decision Making

    Enterprise mobility apps offer significant value on their own, but when integrated into a network with many other applications, objects with sensors, software robots and other data collection technologies, the value of this "network of applications" is multiplied.   The challenge, as identified earlier, is to understand how to use this plethora of real-time data for the purpose of real-time decision-making and operational improvements.  Innovations within many modern military organizations offer lessons for us in the commercial space.

    USAF Colonel John Boyd
    USAF Colonel John Boyd is credited with the concept of the OODA loop. The OODA loop (Observe, Orient, Decide and Act) is a concept originally applied to combat operations and processes that involves analyzing real-time data and rapidly making decisions that enable you to out-maneuver an opponent.

    According to Boyd, decision-making occurs in a recurring cycle of observe, orient, decide and act.  An entity (whether an individual, organization or software robot) that can complete a decision-making cycle quicker - observing and reacting to unfolding events more rapidly than an opponent, can thereby "get inside" the opponent's decision cycle and gain the advantage.

    In the business world, OODA loop is an emerging concept for making better decisions, faster, and managing more effectively.  The ability to observe and react to unfolding events more rapidly than competition requires data collection, communication, analytics and solutions that can use the data to optimize operations. Some of the different enterprise solutions that can exploit IoT data are:
    • Field services solutions
    • Fleet management systems
    • Supply chain management systems
    • Optimized workforce scheduling solutions
    • Solutions using predictive analytics and machine learning
    • Enterprise asset management solutions
    • Plant maintenance systems
    • Facility management solutions
    • CRM solutions
    • Healthcare management systems
    • etc.
    Many of these solutions are already utilizing software robots to quickly accomplish complex tasks and to analyze and act on incoming data.

    Let us walk through a field service scenario together.  Mobile apps and sensors (human and machine) supply the data that enables a field services manager or software robot to observe.  Business analytic systems can be used to help managers or software robots to be oriented as to what the data means, and how it impacts the mission/project/task.  Next the manager or software robot needs to decide what actions to take, and then act.

    OODA Loop
    The “loop” in OODA Loop refers to the fact that this is a continual process. Each time you complete a cycle in the OODA loop you again observe, orient, decide and act based upon the results you see from the prior cycle.  The speed at which you cycle through the loop can be greatly enhanced by the use of supporting software robots.

    Those involved in agile development projects will recognize these cycles.  If the results are positive, you can continue down that path and improve it. If the results are negative, you quickly adjust. It is a fast moving process of trial, error and adjustment until you get the results you want.

    The OODA loop is particularly useful in environments that are unpredictable.  In these working environments, decision-making is often very difficult and without the appropriate training, or automated systems (software robots) - indecision, inaction, inefficiency or even chaos may occurs.  The OODA Loop is a decision-making process that is well suited to helping people or software robots make decisions and act in situations where there is no identified plan or obvious right answer.  

    The military has effectively implemented the OODA Loop decision making process for use in many different areas including air combat, tank warfare, maneuver warfare strategies and daily in Special Forces operations.  Today, predictive analytics and software robots are utilizing OODA Loops with machine learning to cycle through analysis, decision-making and action even quicker.  In fact, many of today's most advanced jet fighters require the use of ultra-fast software robots in order to maneuver and stay airborne.

    In a world where nearly 40 percent of the workforce is mobile, companies must learn and implement these concepts in order to successfully manage mobile and remote operations and services.  To be successful implementing and integrating the OODA loop, software robots and Network Centric Operational concepts into field services operations it requires the following:
    1. Data collection systems, sensors (IoT)
    2. Mobile apps 
    3. Real-time mobile communications
    4. GPS tracking - real time knowledge of the location of your mobile workforce, assets and inventories
    5. Real time knowledge of the capabilities and expertise of your mobile workforce
    6. Real time status and progress updates of the tasks, work assignments, projects and the schedules of the mobile workforce
    7. Real time knowledge of the location of all materials, equipment, tools and other assets required to complete specific tasks
    8. Field service management system that assigns, schedules and dispatches specific assignments to specific members of your mobile workforce (often utilizing software robots)
    9. Real-time business analytics 
    10. OODA Loop or similar rapid decision-making processes
    All of the items listed above help provide the real time visibility into your field operations that is required in a networked field services organization practicing OODA Loop strategies and processes.

    One of the remaining challenges, however, with the systems listed above is that humans quickly become overwhelmed by large volumes of data.  Complexity can become an inhibitor to the practice of OODA.  It is not enough to have real time visibility into massive volumes of data, one must be able to orient, or understand what the data means and how it will impact the mission.  That is where automated systems/software robots solve a real problem.  Let's consider the following scenario in a Networked Field Service environment:
    1. A high value bulldozer with an engine sensor wirelessly notifies a service provider that maintenance is needed.
    2. The information is instantly integrated into the work order management system of the service provider.
    3. The business intelligence feature analyzes the scheduling requirements related to the maintenance code that was received.
    4. Automated processes (software robots) quickly search for maintenance updates or alerts from the tractor’s manufacturer that might be related to the received code.
    5. Automated processes (software robots) search for the location of the nearest available and qualified diesel mechanic
    6. Automated processes (software robots) review all qualified mechanics' schedules and compares them for the purpose of optimizing all schedules.
    7. Automated processes (software robots) search for the nearest location where there is an inventory of parts for that particular make and model of tractor.
    8. Automated processes (software robots) looks for the nearest inventory of tools and repair equipment that may be necessary to complete the job.
    9. Automated processes (software robots) search for and reports on the current account status for the customer and any relevant warranty or service contract details.
    10. All of this data is unified and wirelessly sent to the service technician’s smartphone.
    All of the above steps can be performed in seconds, with the right data, analytics, processes, solutions, software robots and strategies, but only when accurate and real-time data is available.

    In summary, the Network Centric Operations concept seeks to translate an information advantage, enabled in part by mobile, IoT, analytics, management solutions and software robotics into a competitive advantage through the robust networking of well informed geographically dispersed people and assets.   This networked organization, using the OODA loop decision making cycle, has the tools necessary to make good and quick decisions in chaotic and unpredictable environments.



    ************************************************************************
    Kevin Benedict
    Writer, Speaker, Senior Analyst
    Digital Transformation, EBA, Center for the Future of Work Cognizant
    View my profile on LinkedIn
    Learn about mobile strategies at MobileEnterpriseStrategies.com
    Follow me on Twitter @krbenedict
    Subscribe to Kevin'sYouTube Channel
    Join the Linkedin Group Strategic Enterprise Mobility
    Join the Google+ Community Mobile Enterprise Strategies

    ***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.

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