Mobile is Causing a Y2K Event in the Enterprise - Forrester Research

I had the privilege last week to present alongside Forrester Research's enterprise mobility expert John McCarthy in London.  I was able to write a full page of notes from his presentation that I share here with you.

• The Age of Cheap and Cheerful Mobile is Over!  It's now going to be complex and innovative which equals expensive.
• "Enterprise Mobility will be as transformative as the introduction of ERPs,” ~ John McCarthy.  Seems CIOs will use enterprise mobility as a driver for change to transform old systems that cannot support the real-time and speed requirements of a mobile era.
• Smart products (i.e. Internet of Things/M2M) are much cheaper today because of the evolution of mobile platforms and security.
• Mobile apps guide people in their physical world.  Merging physical context with virtual intelligence to take the next most likely action (context aware).
• IT Systems will become much more proactive, because they will be context aware and know your patterns and habits.  This will change business processes.
• New mobile apps and businesses like My Taxi, Hailo, Uber offer benefits to both customers and service providers (Taxi drivers), not just to the consumer.
• In markets where products and services are very similar and hard to differentiate, companies like Deutsche Bank, have developed mobile apps for iPads and other tablets to help with financial planning in ways their competition has not.
• Delta Airlines has developed "proactive" capabilities  in their mobile apps.  The apps will automatically show you alternative flights and options when a flight gets canceled, instead of making you do it all manually by standing in line and searching for options with a customer service person.
  
• In the near future - apps will change features and functions based upon context.
• Video cameras can now watch store shelves and alert for stocking issues.
• ERPs are about cost cutting.  The new Mobility and Internet of Things are about revenue generation.
• The dark side of mobility - we are automating huge numbers of people-intensive processes which are eliminating middle-class jobs.
• Lowering high IT costs is no longer the top priority of CIOs, rather meeting customer’s increasing expectations.
• Mobile apps drive 3x to 10x more traffic than the same app on a web/desktop apps.
• People expect the same treatment and functionality regardless of choice of device or platform.
• Companies are still budgeting for mobile apps out of silos, when the projects are really about enterprise-wide transformation.  This must change and be recognized as strategic.
• Old IT model, simple front-end, complex backend.  New model, complex front-end, simple backend so the business can be fast and agile.  This is a requirement of the future.
• The mobile app is the company brand.  Companies need to invest appropriately.  Mobile apps are how we interact many brands.
• Mobile is causing a Y2K event with backend systems.  Many backend systems cannot support the new mobile world and the clock is ticking.
• If the bank branch is in your pocket, why does it also need to be on the corner?
• The average smart TV has 25 software applications in them.
• People are fatter than ever, but they are not joining weight loss programs like Weight Watchers in the same numbers.  Instead, they are downloading mobile apps.
• Systems of records must give-up their maintenance budgets to systems of engagements.

We live in very interesting times!

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Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

View my profile on LinkedIn

Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Browse the Mobile Solution Directory

Join the Linkedin Group Strategic Enterprise Mobility

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

Reducing Conjecture with Enterprise Mobility and M2M

Mission critical enterprise mobility is all about removing blind spots from people and processes. ~Kevin Benedict

The competitive battlefield of 2014 will increasingly involve data.  It will be about collecting, transmitting, analyzing and reporting its meaning faster and more efficiently than competitors.  If you can digitally represent locations, events, activities, resources, job skills, assets, schedules, materials, job statuses, etc., in remote and mobile locations accurately, then you have the ability to introduce incredibly powerful algorithms and AI (artificial intelligence) capabilities that will greatly enhance your ability to optimize processes automatically within your software systems.  WOW!  That was a mouth full!  If you have hundreds of locations, projects and job sites and thousands of assets and remote workers, your future viability as a business is likely to depend on your ability to rapidly and efficiently introduce AI into this environment.

Let me introduce another term to our discussion - machine learning.  It is a branch of artificial intelligence relating to the development of systems that can learn from data and the results of past decisions and actions.  An example is a turn-by-turn navigation system that can re-route the driver based upon traffic conditions.  The system can re-route, analyze the efficiency of the new route, and then store the results for future re-routing considerations.  Another example would be a workforce scheduling system that can dynamically analyze thousands of service technicians schedules based upon SLAs, location, job status, skill levels, available equipment, materials and parts and can automatically adjust everyone's schedules throughout the day to optimize productivity and profits.

In order for AI and machine learning to work, there must be accurate data that digitally represents the situation and environment.  If this data is not available, you have a blind spot.  Blind spots lead management to make decisions based upon conjecture.  Conjecture is defined as a proposition that is unproven.  Conjecture is the enemy of AI and machine learning.  Conjecture means decisions are being made that are unsupported by data.  Often the cause of conjecture in a business is the lack of data due to a blind spot in a process.

If you don't know where an asset is located, you can't schedule its arrival at a job site.  If you don't know what skills or experience a service technician has, then it is hard to predict how long a job will take.  These two simple examples demonstrate a blind spot that is likely to lead to management conjecture.  How do you fix a blind spot?

Blind spots are the lack of visibility, so the answer is to provide visibility.  Technology answers can be in the form of mobile devices, mobile applications, GPS tracking, automated data collection, barcode scanners, wireless M2M sensors, video monitoring, etc.  All of these technology solutions can enhance visibility and situational awareness by providing accurate and timely data which eliminates conjecture from decision-making and supports the introduction of AI and machine learning.

Gartner has ranked ClickSoftware as the leader in the top right quadrant for field service management for the last three years.  This is in large part because of the automation, context aware capabilities and artificial intelligence they continue to enhance and expand in their systems.  You can read more about their AI features here - http://www.clicksoftware.com/982c4fab-524c-4d99-82f6-a033aa347ede/news-press-releases-detail.htm.

What is it going to take to eliminate blind spots and conjecture from your business?

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Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

View my profile on LinkedIn

Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Browse the Mobile Solution Directory

Join the Linkedin Group Strategic Enterprise Mobility

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

The Race for Sensors to Supply Big Data and Enterprise Mobility

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 comes with an inventory of sensors:

• Touch
• Voice
• GPS
• Proximity
• Ambient Light
• Accelerometer
• Magnetometer
• Gyroscopic

I listened to an IT expert in the CIA give a presentation on how they could use the sensors on a typical 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.  SCARY ISN'T IT!?

Those are just a few of the sensors available that integrate the physical world with the digital.  Read this article I wrote to learn more about the incredible capabilities of sensors.

Mobile apps can also be considered the API (application programming interface) between humans and smartphones.  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, and then inputs the results into their mobile app 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 inputs are digitized.

Although there are many powerful sensors in the human body the API is still the human's touch, typing or voice.  The emergence of wearable sensors and smart devices are a way to try to automate the process of data collection so humans are not required to take time and effort to input the data.

Sensors are also connected to the non-physical.  Sensors can connect with time.  Once time reaches a specified place, a digital alarm can go off striking your physical ear with sound waves.  That is making the non-physical inputs, physical.

The challenge for businesses today is to envision how all of these sensors and available real-time data can be used to improve 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 disruptions of tomorrow are likely coming from digital disruptions - sensors, code halos, big data and mobile devices and wearables.

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

***Have you seen the new Mobile Solution Directory here http://mobilesolutiondirectory.blogspot.com/?

*************************************************************

Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

View Linkedin Profile

Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Join the Linkedin Group Strategic Enterprise Mobility

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

Satellites, GPS Tracking, Artificial Intelligence and Mobile Technologies

My good friend J.D. Axford, a civil engineer and hero of all ducks for his wetlands work, sent me a very interesting (if you are into GPS tracking, GIS, mobile technology, artificial intelligence, accelerometers, etc.) article he wrote on how the physical is meeting the digital in the world of construction and engineering today.  I am including it here for your pleasure and education.

Compaction, in heavy construction, is the application of energy to soil, crushed rock, or asphalt to increase density by driving out air, which enables the finished, compacted material to support buildings, roadways, and other structures. Compaction is specified as a percentage of the maximum dry density determined in the lab.

During construction, compaction is most often measured using a nuclear densitometer. Other reliable methods include the use of sand cone (ASTM D-1556) and rubber balloon (ASTM D-2167) methodologies; less formal tests used in the field include soil probes (a pointed steel rod pushed into the ground to gage penetration resistance and therefore estimate compaction), proof-rolling with loaded dump trucks while observing deflection, and even boot-heels. These all are necessarily spot-checks; consistency is sought by controlling the compaction process.  This requires the roller operator’s ability to track speed and passes over each section while estimating compaction, leading to both over- and under-compaction. Near-constant inspection is usually needed, and even so, compaction is a frequent source of job site disagreement.

Intelligent compaction (IC) is a system growing in use which combines on-board GPS, computers, and axle-mounted accelerometers to provide continuously-controlled compaction. The accelerometers measure stiffness, and indirect measurement of density, and feed that information to the computer, which uses GPS to produce a color-coded map of the working area; the colors are used to provide an intuitive depiction of areas already meeting specifications, and those needing more compaction. For asphalt work, IC systems (there are approximately eight US equipment vendors developing and selling IC), infrared sensors measure (and the computer maps) the asphalt temperature, a critical data set in ensuring timely compaction as the material cools.

As is normal, a test zone is compacted at the start of the overall compaction effort to determine the number of passes and speed the material requires to meet specifications. That information is entered into the on-board IC system as the baseline against which future work areas are compared and mapped. This eliminates guesswork, eliminates overwork, and improves the homogeneity of the finished product, saving money for the contractor and improving the service life of the compacted product.

Intelligent compaction, requires mobile technologies, GPS tracking and artificial intelligence to calculate all kinds of accelerometer and speed data, location and project requirements.  This is another example of how the physical is meeting the digital and improving processes.  You can learn more about how artificial intelligence is being integrated into field services by ClickSoftware here.

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Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

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Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Join the Linkedin Group Strategic Enterprise Mobility

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

Where the Physical Meets the Digital in Field Services and Asset Management

I am fascinated by the notion of the physical world converging with the digital world and the benefits that become possible as a result.  Not in the context of a humanoid weeding my garden, although that would be nice, but in the context of making better business management decisions based on more efficient data collection and reporting.  The term digital transformation is often used to describe this convergence.

Think of growing the best possible garden full of award winning fruits and vegetables.  The garden may consist of some physical things like dirt, seeds, containers, plants and tools, but the key to success is the information about the garden.  The information about the soil, types of plants or seeds, appropriate time to plant and harvest, weeding and watering schedules, the best fertilizers to use based upon the soil conditions etc.  This information can be collected and input into a software application as digital information.  Once digital, software applications can analyze this information and create schedules and plans on how to optimize the production of the garden.  Business operations are much the same.  The more data that can be collected and analyzed on location, physical assets and facilities, environmental conditions, tasks, status, etc, the better planning and optimization can be done by software applications utilizing artificial intelligence.

Integrating Geospatial with ERPs

Let's consider utilities and other geographically dispersed operations.  Effective data collection, management, analysis, and reporting of data is critical.  They own and management data-driven systems of pipes and wires, poles, valves, substations and switches all associated with data such as location, service history, asset details, maintenance records, applicable product warranties and history.

Utilities must know a massive amount of geospatial information about their assets and the environment around them.  Think about an underground gas line.  The utility needs to know the exact location of it, creeks, rivers, roads, property owners and property lines, access routes, location relative to other construction sites, environmental impact studies and issues, minor and major transportation lines crossed, just to mention a few data points.  In addition, a lot of information is dynamic like new construction sites, road building, digging, erosion, etc.  Not only must the utility collect and store static information like asset details, but dynamic data about activities and tasks around it.  Wow!  You can quickly see that efficient information  collection is critical.

Efficiently operating a utility grid is mostly about implementing an efficient logistics of information system connecting field data collection and management and planning solutions in the office.  If you are a sub-contractor for services, it is also the way you get paid.

Today many are considering the use of tablets for collecting and querying required field data.  The problem is tablets still have painful limitations. First, while tablets have the computing power of laptops, their memory remains limited, which impacts their capabilities when working with large geospatial databases unless you purchase specialized geospatial software purpose-built for tablets.  Secondly, connectivity in the field is often intermittent, while geospatial data access needs are constant.  This necessitates a robust offline mobile app and data storage capability often missing from tablets.  And finally, there are multiple tablet operating systems available, which often dictate the type of applications, databases and geospatial applications that can be used by your workforce.

If your organization is considering the use of tablets in the field look for applications that can support multiple tablet operating systems, offline data editing and data collection and integration with all of your required ERPs and geospatial enterprise applications and databases.

Now let's get back to the notion of the physical meeting the digital.  In a utility, the digital information (code halos) related to a physical asset and the tasks around it are the keys to planning, scheduling and maintaining it for optimized productivity.  That means efficient data collection is critical to digitizing your physical environment and gaining the benefits of artificial intelligence built into your planning, scheduling and asset management solutions.

Today efficient data collection can be facilitated through M2M (machine-to-machine) embedded wireless chips integrated with sensors that automatically report on conditions and statuses of equipment, assets and facilities, and by field workers using smartphones, rugged laptops or tablets.

How efficient is your data collection system?  Are there gaps that are preventing you from fully digitizing your physical operational area and leaving you with geographical and operational blind spots?

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Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

View Linkedin Profile

Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Join the Linkedin Group Strategic Enterprise Mobility

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

Enterprise Mobility, Network Centric Operations and Decision Making

Mobile apps for the enterprise can offer significant value on their own, but when integrated together into a network (network centric operations) with many other applications, the IoT (internet of things) and other data collection technologies, this network of applications can offer exponentially greater visibility and value to an organization.   The challenge is to understand how to use this plethora of data for the purpose of good operational decision-making.  Modern military strategies offer some useful insights for us.

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 operation processes. Today it is also applied to commercial operations and learning processes where significant value has been realized.

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

In the business world, OODA loop is an emerging concept for making decisions and managing fast changing field services, projects and mobile operations.  Today the ability to observe events from afar benefits from mobile technologies and connected devices such as:

• Wireless networks
• IoT
• Mobile data collection solutions (mobile inspection forms, barcode scanners, RFID, GPS, etc.)
• Mobile field services applications
• Mobile business intelligence applications
• Enterprise asset management solutions
• Plant maintenance systems
• Mobile CRM
• GPS location tracking technologies
• etc.

Mobile data collection and the IoT supply the data that enables a field services or plant manager to observe from afar.  

The next step in the OODA loop is orientation.  The manager needs to be oriented as to what the data means, and how it impacts the mission.  

Decide - now that you have the necessary data and you understand what it means, you must make a good data-driven-decision.  

Act - take action without delay based upon all the data you have received, its business meaning and the decision you have made. 

The “loop” refers to the fact that this is a continuous process.  The loop or cycle never stops.  Each time you complete a cycle in the OODA loop you observe, orient, decide and act again based upon the results you see from the prior cycle.  If the results are positive, you can continue down that path and improve it.  If the results are negative, you quickly adjust and review the results again.  It is a fast moving process of trial, error and adjustment until you get the results you want.  Not dissimilar to the agile programming methodology.

The OODA loop is particularly useful in environments that are chaotic and unpredictable.  In these working environments, decision making is often very difficult and without appropriate training paralysis in decision-making results and nothing gets done.  The OODA loop is a decision making process that is well suited for helping people make decisions and acting in situations where there is no existing road map to follow.

   

The military has effectively utilized the OODA loop decision making processes in the chaos of battle found in air combat, tank warfare and daily in Special Forces operations.  There is a lot to be learned from these experiences in decision-making.

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 operations and services from afar.  To be successful implementing and integrating the OODA loop and Network Centric Operational concepts into your field services operations requires the following:

1. Data collection systems and processes.
2. Real time knowledge of the location of your mobile workforce, assets and inventories.
3. Real time knowledge of the capabilities and expertise of your mobile workforce.
4. Real time status and progress updates of the tasks, work assignments and schedules of the mobile workforce.
5. Real time knowledge of the location of all inventory, equipment, tools and other assets required to complete specific tasks.
6. Work order management system that assigns, schedules and dispatches specific assignments to specific members of your mobile workforce.
7. Business intelligence software applications for analyzing data collected in the field.

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 management decision making.

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, as one must be able to orient and understand what the data means and how it will impact the mission.  Business intelligence software, context aware and artificial intelligence capabilities all fit in here. 

*************************************************************

Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

View Linkedin Profile

Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Join the Linkedin Group Strategic Enterprise Mobility

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

Enterprise Mobility, IoT and the Network Centric Operation

Manufacturing plants, vehicles, high valued equipment and other assets can take advantage of the IoT (Internet of Things) and low cost embedded mobile devices to provide visibility into operations and events in remote locations.  M2M (machine to machine) data can report on anything that a sensor can read for example: operational status, location, environment (pressure, heat, cold, wet, dry, etc.), hours of operation, maintenance and repair needs. This data can then alert field managers and service teams when there is a problem or event that requires their attention.
 
The location of mobile workforces can also be tracked via smartphones or vehicle tracking systems which enables management to better understand how to optimize the use of experts and assets across a geographic area.

Today wireless remote sensors are capable of bi-directional data exchanges.  Sensors can both send data to the central server and receive data in the form of machine commands.  In many cases remote sensors can receive commands from central servers to adjust settings or perform other functions via wireless data exchanges.  This opens up a wide area of possibilities.  Today we see irrigation canal gates, greenhouses and other facilities and assets controlled remotely using this technology.

M2M is a way of connecting physical and digital things to each other wirelessly through a network. These connections, and the data exchanged, can provide real time visibility and access to information about the physical world and the environments around the M2M enabled objects in it.  This is an important component used to develop full situational awareness of a given area of operations.  Used in the context of an electrical grid, enterprise asset management system, plant maintenance, field service automation system, or any other mobile workforce management solution, this data can lead to innovations and gains in efficiency and productivity that were never before possible.

Juniper Research predicted that the number of M2M and embedded mobile devices will rise to approximately 412 million globally by 2014.  ABI Research used a more conservative set of numbers and says that there were approximately 71 million cumulative M2M connections in 2009 and predicts this will rise to about 225 million by 2014.  GSMA predicted that there will be over 50 billion embedded mobile devices by 2025.  All of these predictions represent big numbers and a lot of data. The challenge for managers today is how to turn this high volume of available data into actionable intelligence.

Some of the key markets for M2M systems are:

• Utilities/Smart grids
• Fleet management/Automotive systems 
• Equipment monitoring/Plant maintenance
• Connected homes/Home Energy Management Systems (HEMS)
• Healthcare - Remote patient and health monitoring, medical equipment monitoring
• Vending/POS
• Remote asset management monitoring
• Security systems
• Consumer electronics (eReaders, Wireless Printers, Appliances, etc.) 

In a world filled with M2M data feeds, the question is what can you do with all of this data?  Where can this data provide value?  This is where business intelligence applications are needed - solutions that have the capacity to immediately analyze vast amounts of data and recommend how best to use it for optimal operational efficiencies.

I am seeing companies like ClickSoftware embed artificial intelligence into their scheduling and workforce optimization and field services solutions.  They use collected data to predict the needs of the field services workers.  M2M data enhances these kind of solutions with additional data provided by sensors on machines, in plants and across utility grids.  ClickSoftware has a new software component titled ClickButler designed to predict, based on a wide range of collected data, the information most relevant and needed by your mobile field services teams.  This is just the beginning of a new wave of innovation.

*************************************************************

Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

View Linkedin Profile

Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Join the Linkedin Group Strategic Enterprise Mobility

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

The Industrial Internet and SMAC - Social, Mobile, Analytics and Cloud

The Industrial Internet refers to the world of connected sensors on people, equipment, machines, parts, assets, vehicles, inventory, etc.  These items are connected by embedded wireless chips that monitor sensors and wirelessly send data to a server somewhere in the world.  Here is an example of how one of the largest companies in the world is utilizing the industrial Internet.

Every major part of a GE jet engine, locomotive or turbine is equipped with wireless sensors that continuously measure and wirelessly send every aspect of performance to a central server that is often in the cloud. As the data is received by the server, it is analyzed by big data analytical solutions and the results are used to improve everything from the flight path to energy efficiency.

This same kind of Industrial Internet platform could also be used to monitor and improve the health of large populations of people as well.  I think immediately of the elderly, those with chronic diseases, those recuperating from any kind of health issue.  If they can be monitored and cared for while staying at home, that is a far more comfortable and less expensive place to stay for many.  I can foresee a time when we will subscribe our elderly parents to a full time health monitoring plan.  Our elderly parents will wear a bracelet that contains a large number of sensors that monitor a spectrum of things from location to activity levels, temperature, pulse, heart rate, etc.

The industrial Internet will result in massive amounts of new data being added to wireless networks.  MNOs (mobile network operators) make less money supporting a small embedded wireless chip in a piece of equipment than adding a new iPhone customer, but the embedded wireless sensor chip is unlikely to change carriers, call a support center, or dispute an international call; so although the embedded wireless chip is not as profitable as a smartphone customer, the cost of sales and support are far lower.  This area is considered one of the major growth areas for mobile network operators and is currently being heavily promoted by MNOs.

In the enterprise, the ability to know about your operational area is critical.  If you are managing a fleet, it is important to know where they are, which vehicles need new tires, oil changes and other maintenance.  It is important to know and plan for how much money you need to spend each month/year on maintenance and replacement costs.  If you know the location of your fleet, you are better able to provide least cost routing, improve scheduling, avoid traffic and weather hazards and improve overall profitability.  The industrial Internet connects managers with real data, in real-time.  The Industrial Internet proves that knowledge is power.

What is the connection of the Industrial Internet to SMAC (social, mobile, analytics and cloud)?  Let's consider the description above of how GE is using the Industrial Internet.  Every major part of a GE manufactured jet engine has a wireless sensor.  These sensors are continuously sending data to a server.  Many of those major parts are manufactured by third parties - contract manufacturers.  When strange data starts coming in from several parts - I can image there is an immediate need to analyze, communicate and collaborate among many different teams.  As many of your smartest key people are mobile and traveling, you will need mobile communications and the ability to review shared data (a good use case for a cloud-based collaboration environment).

The Industrial Internet has the ability to transform working environments, strategies, industries, processes and methodologies in big ways, just like mobile devices have changed entire businesses, industries and processes.  These two trends are not separate. They build off each other, and because of this the changes and transformations introduced will not be linear.  They will introduce exponential change at a pace most are not equipped to handle.

*************************************************************

Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

View Linkedin Profile

Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Join the Linkedin Group Strategic Enterprise Mobility

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

Wearable Devices, Mobile Apps, Sensors and Clothing Companies

Nike FuelBand

As I was working this morning I become annoyed that my Nike FuelBand kept rubbing against my MacBook Pro keyboard while I was typing.  The Nike FuelBand is my first wearable (M2M or IoT) device.  It is a bluetooth enabled sensor inside a wristband.  The sensor has an accelerometer that records the level of activities you participate in during a 24 hour period.  When you press a button it syncs its recorded data with your iPhone.  The iPhone in turn uploads the FuelBand data into your Nike account in the cloud.

Once the data enters your mobile app on the iPhone and/or your account in the cloud, it analyzes it against past and future activities, recorded goals and other measurements.  On nearly every screen you are encouraged to be social, and to share your activity data with friends, family and the Nike social family.  There is also a whole lot of gamification going on.  You can escape and survive all kinds of dangers presented in a game on the Nike cloud site by keeping your activities up and meeting your goals.

One of the challenges, however, is the Nike FuelBand does not have a GPS tracking system (although your iPhone does), nor does it know you are engaged in certain activities like riding a bike, either on the road or a stationary one.  There is no method for manually entering activities that are not easily monitored by the Nike FuelBand.  I solved a few of those problems, after a little research, by integrating the Nike FuelBand app and account, with my Nike Running app (which uses my iPhone GPS capability).  I could then precisely track times, distances, paces and routes. Both the FuelBand and the Running app are integrated through my Nike cloud account so they can both access the same data and monitor my activities accurately.

I was, however, still faced with the problem of recording and tracking exercises and activities that are not accurately captured by the Nike FuelBand or the Nike Running app on my iPhone.  I eventually discovered a solution, however, by finding that I could integrate my Lose It! mobile app with my Nike cloud account as well.  Lose It! is a great app for manually tracking calories consumed and exercises completed.  Lose It! does not have its own hardware or sensors, but integrating it (a simple check box) with my Nike cloud based account enabled it to share data I manually entered, and for the Lose It! app to read and integrate sensor data from my Nike Running app and my Nike FuelBand (wearable sensor).

Let's review the components:

• iPhone and GPS sensor
• Nike FuelBand (bluetooth enabled accelerometer sensor in a wristband that communicates with your iPhone) to monitor activity levels
• Nike Running iPhone app that uses the iPhone GPS to track distance, speed, pace, etc.
• Nike cloud based account to aggregate, analyze, report on and archive the data
• Lose It! iPhone app that enables you to manually enter foods/calories and exercises.  It can be integrated with your Nike cloud based account so exercises, activity levels and running data can be more accurate and shared.

I believe the wearable mobile device and exercise/activity apps market will mature and these disparate capabilities will soon converge into a single wearable device and a full functional app.  Today, however, us early adopters have the fun of discovering their limitations, reviewing each update, and finding work-a-rounds.

It is quite interesting to me, that a clothing/shoe company, Nike in this case, is so involved in high tech sensors, mobile hardware, cloud based solutions, social and gaming platforms and analytics.  It is the beginnings of the digitization of clothing.  I know Under Armor is also deeply involved in these digital transformations.

These clothing companies understand that their brands are increasingly going to be judged by the quality of their digital presence, rather than just the quality of their physical designs and materials.  It is a different world that we live in today.   One that we should all be pondering.

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Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

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Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

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

Mobility, The Internet of Things and Code Halos

Each of us are surrounded by our digital choices, preferences, activities, history and experiences that are captured as data and analyzed by the systems and websites we use.  Why did Google, a company known for its search engine, develop a mobile operating system?  They recognized the importance of mobility, and the fact that we would be accessing all things digital through these devices.  They wanted to optimize their ability to collect data and analyze it through mobile devices and the mobile web.

Here is a recent excerpt from an article written by Ben Pring on this subject, "What one key characteristic separates today’s high-flying outperformers – such as Apple, Google, Amazon, Netflix and Pandora – from fast-followers, wannabes, and laggards? It’s a precision focus on the information that surrounds people, organizations, products and processes – what we call Code Halos ™."

My colleagues Malcolm Frank, Ben Pring and Paul Roehrig recently recorded an excellent short video on this subject to help us understand the role of "Code Halos" on the web, in mobility and the Internet of Things.

Video Link: http://youtu.be/XYwiDJ7UWHo



To read more about SMAC (social, mobile, analytics and cloud) strategies and trends, Code Halos and other mega-trends click here, or visit my article library on these subjects here.

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Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

View Linkedin Profile

Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Join the Linkedin Group Strategic Enterprise Mobility

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

Connecting the Dots Between Enterprise Mobility and IoT

Lisbon, Portugal

I had the privilege of having breakfast with Dr. Moshe BenBassat, Founder/CEO of ClickSoftware, on a deck overlooking the Mediterranean this morning.  Over an English breakfast, Dr. BenBassat shared that back in 1985 his team had developed software tools to diagnose equipment for the military.  It seems two thirds of all parts replaced were unnecessary.  The parts were being replaced in an effort to find and fix a problem without having first properly diagnosed it.  His team was tasked with designing an artificial intelligence system to process and analyze data in order to properly diagnose problems so only the required parts would be replaced.

In 1985 there were huge challenges to this task.  There were not wireless data networks commercially available.  There was not a lot of data available.  There were no IoT (Internet of Things) solutions deployed to gather data, there were not "big data" systems that could crunch numbers in seconds and there were no IBM Watson artificial intelligence systems available to diagnose problems and come up with answers in seconds.  Dr. BenBassat's team was successful, but the final solutions could only be used in areas where there was a lot of time available to come up with an answer.  The system couldn't work in a real-time environment.

A lot has changed since 1985.  Today, equipment/assets, using embedded wireless chips and sensors (M2M), can report on itself and wirelessly send data to a server.  This data can be processed in real-time, analyzed and the diagnosis can be shared wirelessly to the mobile device of a service technician.

Today, with big data analysis, service companies don't have to just rely on manufactures' data to understand when maintenance or repairs are required.  If you have thousands of wind turbines operating and reporting their sensor and system data to your server, it does not take a lot of time to start seeing patterns using big data analysis.  These patterns can help you diagnoses problems, and better plan your future maintenance and repairs in a manner that does not result in unplanned shut-downs.  This results in improved productivity and output.

Dr. BenBassat's system designs, math and algorithms for artificial intelligence were accurate and powerful in 1985, but the technology was not there.  It is a different story today.

Today, it is not the lack of technology that prevents these productivity gains, rather it is the lack of management connecting the dots to existing systems and technologies.  I teach SMAC (social, mobile, analytic, cloud) strategies just about every week somewhere in the world.  Most of my work is not teaching about new technologies, but rather helping CIOs connect the dots to what is already available today.

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Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

View Linkedin Profile

Read the whitepaper on mobile, social, analytics and cloud strategies Don't Get SMACked

Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Join the Linkedin Group Strategic Enterprise Mobility

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

Mobile Expert Video Series: Puneet Suppal

In this interview recorded last week at SAPPHIRE NOW 2013, I ask SAP Hana Guru Puneet Suppal about the connection between enterprise mobility, M2M or IoT, real-time business and SAP Hana.  Enjoy!

Video Link: http://youtu.be/-uqIRD7wRgs

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Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

View Linkedin Profile

Read the whitepaper on mobile, social, analytics and cloud strategies Don't Get SMACked

Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Join the Linkedin Group Strategic Enterprise Mobility

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

SAP M2M Expert Suhas Uliyar Shares Strategies for the Internet of Things

This is one of the most informative interviews I have recorded on the subject of the IoT (Internet of Things).  IoT is a big subject here at SAPPHIRE NOW 2013.  In this interview Suhas Uliyar shares what an end-to-end M2M (machine to machine) solution looks like in an SAP world.

Learn how the SAP Mobile Platform, Hana, Syclo, Right Hemisphere/ SAP Visual Enterprise, Afaria, Augmented Reality, Mapping, cloud computing and SAP NetWeaver all work together in an M2M solution.

Video Link: http://youtu.be/vJMCzQS-9wA

*************************************************************

Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

View Linkedin Profile

Read the whitepaper on mobile, social, analytics and cloud strategies Don't Get SMACked

Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Join the Linkedin Group Strategic Enterprise Mobility

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

Advanced Mobile Strategies and Integrated Sensors

Last week I watched a presentation recorded at GigaOm Structure:Data conference featuring Gus Hunt, CTO of the Central Intelligence Agency (CIA).  In his presentation, he identified SMAC (social, mobile, big data analytics, and cloud) as the culprit for the massive increase in available data in the world.  He explained that the average smartphone generates huge quantities of data from the following embedded sensors:

• proximity sensors
• 3-axis accelerometer sensors
• touch sensors
• image sensors
• microphone sensors
• light sensors
• GPS (geo-location) sensors

You can imagine, with the billions of phones around the world, how much additional data is produced each day!  Now add the mass volumes coming out of social media!

Hunt went on to say there is a time-value-of-data.  This is an important concept for us to understand.  The value of data is worth more this second, than it is worth in two weeks.  When I activate the GPS on my iPhone, I want something to happen now not tomorrow.  The GPS sensor needs to give me immediate feedback.  Likewise, information about the location of a bad guy this second is much more valuable than where he was last month.

Have you ever had a slow GPS navigation system?  I have.  It told me to turn after I passed by the exit. GRRRRRR!

The CIA has a unique mission that involves filtering through mass volumes of big data sources for information that is important to our national security and interests.  Hunt identified seven universal constructs for analytics, or ways of organizing data that I found very interesting:

1. People
2. Places
3. Organizations
4. Times
5. Events
6. Concepts (value judgements - good or bad)
7. Things (Internet of Things)

In my SMAC strategy sessions, I spend a lot of time educating my audience on five of these seven.  I might now need to re-think how to incorporate organizations (project teams?) and concepts into my sessions as well.

In the context of enterprise mobility, the location of your people and places (think job sites, customer locations, supply depots, etc.) are all very important.  However, time and events are equally important for project management and scheduling.   What time did you start and finish a job?  How long will it take to drive to the next job site?  What did you do while at the job site?  Did you complete the task?  All of these things are very important.

It is important to again look at what Hunt said about the time-value of data.  You cannot optimize a service technician's schedule if you don't know when he starts or finishes a job.  You can't optimize his driving route if you don't know when he is driving.

Today GIS (Geospatial information systems) are beginning to associate where things are at a particular moment in time, and how they are related to other objects, people, events, etc, around them.  These relationships will be very important.  For example, a construction manager may require a backhoe to continue on a project.  The backhoe is three hours from being on the job site.  This is important information for planning and scheduling.  It is important data that has a high time value if known in advance. However, it has very little value if it is only known after the fact.

What are the relationships between the construction manager, project, P&L and backhoe?  The manager owns the project and project P&L.  The project is on hold until the backhoe arrives, which jeopardizes the profitability and completion of the project.

All of this data about location, things, relationships and times is critical to optimizing projects and plans.

In the very near future, software developers will need to be much more familiar with the physical world, as the digital and physical are integrating around real-world data.  I will emphasize again that the value of the data is dependent upon the speed in which it is collected, analyzed and shared with those who can use it in the field.  But that is not all!  Here is a final quote from Mr. Hunt,  “The power of big data can only be fully realized when it is in the hands of the average person.”

Mobile strategies are not just about managing smartphones and securing data between the office and mobile workers.  It is about all of the things identified in this article and more.  It is about the time, location and relationships between moving players, concepts and events.  This is where the real fun is today!

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Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

View Linkedin Profile

Read the whitepaper on mobile, social, analytics and cloud strategies Don't Get SMACked

Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Join the Linkedin Group Strategic Enterprise Mobility

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

Predicting the Future of Enterprise Mobility

Figure 1 - Smartphones as
Internet of Things Hubs

How many advertisements for automobiles today promote the fact their cars are horseless carriages?  None! Why?  It is an assumption that your automobile will be horseless.  The same is happening today with mobile apps.  Who would develop a work order management or scheduling system today that does not support mobile?  Who would create business intelligence dashboards for executives that were not mobile?

Today it is a mobile first world.  Our first considerations for software app designs are:

• What mobile devices will be used?
• How do I integrate wirelessly with my back-end data sources and systems?
• What onboard and remote sensors can I integrate into the app?
• How do I secure it?

If all software apps are soon to be mobile, where will we find the next wave of innovation beyond traditional mobile apps and enterprise mobility platforms?  I believe it will come from sensors and integrating the physical world with the digital.

I have been working in the field of enterprise mobility for the past 13 years.  Early on there were very few sensors in mobile devices.  The sensors were the humans users, bluetooth add-ons, and barcode and RFID scanners.  Today, however, there are many built-in sensors in each of our smartphones and thousands of different kinds of data collection sensors available through the Internet of Things.

Let's ponder how our mobile apps are going to start interacting more with the physical world.  Sensors in parking lots can already notify us of available parking spaces.  Buildings can quickly report their own needs and status with embedded structural sensors that monitor vibration levels, energy consumption, security and more.  Your cars can wirelessly report their location, status and maintenance needs directly to your smartphone.  In urban areas sound sensors can lead you to quiet areas or noisy areas.  Traffic sensors can help you find the least congested routes.  Opt-in GPS tracking can help you navigate and meet up with friends and family members.  Weather sensors report the exact conditions at millions of locations.  Integrated with predictive analytics, you can anticipate weather conditions for the next week.  Using mobile banking apps, NFC, ATM sensors and POS sensors, you can be notified any and every time there is a transaction on your account - what was purchased, where and for how much.

Your smartphone is changing from a simple communication device, media center and personal digital assistance, to a hub between the physical and digital world.  That development opens up all kinds of interesting opportunities to ponder.  It is on the very edge of digital transformation where the integration between the physical and the digital happens where the next wave of innovation lies (see figure 1).

In the future software developers will become more and more like geographers and intelligence analyst as they increasingly work with real-world data.  They will be blending geospatial data, live remote sensor data and process data to create and understand relationships about where things are, how they are connected and what that data means to the success of the mission or plan.  This information will all be available on a smartphone and tablet near you.

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Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

View Linkedin Profile

Read the whitepaper on mobile, social, analytics and cloud strategies Don't Get SMACked

Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Join the Linkedin Group Strategic Enterprise Mobility

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

Google X, Hyper Spectral Remote Sensing - It's All About Sensors, Mobile Technologies and Big Data

Did you sign up to beta test Google Glasses?  Have you ridden in Google's driverless cars?  Your answer to both questions is likely not yet, but these are two very interesting innovations coming out of Google X (Google X is a secret facility run by Google thought to be located somewhere in the Bay Area of Northern California) that have been widely covered by the media.

These two innovations demonstrate the combination of mobile communications, the Internet, mobile software apps, all kinds of sensors, augmented reality, artificial intelligence and real time analytics.  I think the coolest components of these innovations are rarely highlighted - the integrated sensors that make them possible.

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.

Developments in hyper spectral sensors are being supported by innovations in remote sensing combined with GIS (geospatial information systems) and Big Data analytics. 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.

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.

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.

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 scary, 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.

Google Glasses do not yet have hyper spectral remote sensing cameras built-in, but they do have sensors that are limited only by their physical size and weight, and include augmented reality connected with Big Data.

The world is quickly being documented, digitized and given a digital persona.  The digital persona is only as accurate as the sensors that are being used.  The more accurate and connected sensors are to Big Data analytical systems, the more the Big Brothers know about us and everything around us.

How about we all work together to ensure that our Big Brothers are good big brothers.  What do you say?

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Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

View Linkedin Profile

Read the whitepaper on mobile, social, analytics and cloud strategies Don't Get SMACked

Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Join the Linkedin Group Strategic Enterprise Mobility

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

Kevin Benedict's Mobile World Congress 2013 Interviews: Fred Yentz, Part 2

M2M and the Internet of Things were central topics at the Mobile World Congress 2013.  SAP was showing off several demonstrations on how machine data, wirelessly sent to SAP, could be analyzed in real-time using SAP Hana.  In this interview, M2M expert and ILS Technology CEO Fred Yentz discusses the concept of "Sensor-to-CIO."  Grab some popcorn!

Video Link: http://youtu.be/cZOCxiUkViQ

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Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

View Linkedin Profile

Read the whitepaper on mobile, social, analytics and cloud strategies Don't Get SMACked

Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Join the Linkedin Group Strategic Enterprise Mobility

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

Kevin Benedict's Mobile World Congress 2013 Interviews: Charlie McNiff

It was interesting how much of the Mobile World Congress this year was about M2M and the Internet of Things.  I guess it makes sense from a teleco perspective, mobile data is mobile data, whether it comes from a mobile app on a smartphone or a piece of heavy equipment wirelessly reporting its maintenance needs.

I have often written over the years that M2M and enterprise mobility would eventually converge.  This year they certainly did at the MWC 2013 event.  Mobile data coming in from remote workers and assets is all valuable to the enterprise.  With the right business analytics solution your managers can use this real-time data to make good data driven decisions.

At the show, SAP connected their M2M initiative with their Hana platform to deliver real-time analytics to the Port of Hamburg in Germany.  The demonstration was in the Connected City at the show. The solution was used to track incoming cargo containers, truck parking spaces and truck locations.  The M2M data coming in wirelessly from these three areas was analyzed in seconds and used to improve efficiencies in the logistical processes.

In this short video, I interview SAP partner ILS Technology about where they see growth in the M2M industry.  Grab some popcorn!

Video Link: http://youtu.be/EEdG1rWzTdc

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Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

View Linkedin Profile

Read the insightful whitepaper on mobile, social, analytics and cloud strategies Don't Get SMACked

Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Join the Linkedin Group Strategic Enterprise Mobility

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

Notes and Videos from the Mobile World Congress 2013, Part 1

Yesterday was the first day of the Mobile World Congress 2013 in Barcelona.  It is reported there are 70,000 people here.  I counted 69,901.  I explored miles of aisles filled with mobile and wireless software vendors, equipment, accessories and devices manufacturers over 8 massive halls.

I have been tracking down mobility experts to interview.  I tried to upload some of the interviews yesterday, but my hotel wireless appeared just enough to tease me before disappearing again.

Today I will be speaking at the Power of Enterprise Mobility session in Hall 8.  There are seats for 250, but over 2,000 registered for it.  Yikes!

Here is the first of many interviews I recorded with experts in mobility and M2M.  This interview is with M2M / Internet of Things guru and Fred Yentz, CEO of ILS Technology.

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Kevin Benedict, Head Analyst for Social, Mobile, Analytics and Cloud (SMAC) Cognizant

View Linkedin Profile

Read the insightful whitepaper on mobile, social, analytics and cloud strategies Don't Get SMACked

Learn about mobile strategies at MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Join the Linkedin Group Strategic Enterprise Mobility

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

Mobile Devices, Management Structures and SMAC, Part 3

I just finished a book titled Social Business By Design by Dion Hinchcliffe and Peter Kim.  I recommend this book to anyone interested in the impact SMAC (social, mobile, analytics and cloud) is going to have on your industry, market and company.  Mobile devices have empowered social networking platforms for both consumers and the enterprise.  The SMAC stack is shaking up retailing, banking, healthcare, media, government, insurance, etc.  Industries that are primarily about information will experience the biggest initial impacts of this transformation.

Figure 1.

One of the insights I gained from this book is the impact social enterprise collaboration tools and internal social networking platforms can have on management structures.  In Figure 1, a typical hierarchical organizational chart is depicted.  Ideas and innovations that come from the people at the bottom of the chart, where most people are, have a great deal of trouble moving up and it can take a long time to move up.  At each level there is a gatekeeper.   This gatekeeper, has his/her own agendas, political considerations, priorities, limited time, poor memory, and communication challenges.  Many good ideas and innovations simply die with these gatekeepers.  The potential economic costs due to inefficient and slow communications in this model is enormous.  Just think about how many innovations, good ideas and problems could be quickly solved if the right people with the right knowledge could be instantly notified and involved.

In Figure 2 you have a simple illustration of an organizational chart when a social networking site, or social enterprise collaboration platform is involved.  Anyone can share an idea with the entire group.  The idea can be openly discussed, debated and voted on.  Innovations and ideas get their fair consideration.  In this model, the power in the organization is not dependent on the gatekeepers and titles people have had bestowed upon them, but with those that have the best ideas and answers.

The people with the best ideas and a willingness to share in social networking environments gain a reputation and credibility that raises their social power, or as one social media vendor calls it "Klout."  The power structure changes when information is in an open social democracy.

SAP's SCN (SAP Community Network) is an example of the power of social networking and collaboration tools in use.  Here is a description of its purpose and value as described in the book Social Business By Design, "The goal was to enlist customers and other interested parties to come together online and share ideas and solve problems. In this way SAP could engage and mobilize the people who were smartest about using its products in the field. Customers could then work together directly and exchange valuable knowledge."

Note that many problems SAP users have, can be more quickly and efficiently resolved by other users on the network.  This helps the end user, and reduces support costs on SAP.  It is a win-win.  The more time that goes by, the larger the database of answers and useful content grows which just increases its value for the entire community.

SAP is one of the first companies to identify specific ROIs from implementing social collaboration platforms.  Again from the book Social Business By Design, "SAP cites SCN for improving customer retention, creating efficiency, and driving top-line growth and revenue."

Let's now reflect on the role of mobile devices in this process.  In days gone by, the people with the power were those "in" the corporate office. Those actually physically in the building.  Slow and tightly controlled communications that followed the hierarchy of the organizational chart meant often the powerful needed to be in the room where data was available and decisions were made.  However, in today's mobile and social world, where the most knowledgable people, and those with the most "social" power and influence in the company are often traveling and spending their time with customers, prospects and partners, mobile access to important data, social networks and collaboration sites enable them to continue to provide value to the company and to the community from anywhere.

Mobile technologies are enabling the abstraction of power from a management hierarchy, or a building location to wherever there are the best ideas and people are willing to share them.  That means the corporate power structures have now been digitized, mobilized and socialized.  If you want to be somebody in the company, you will need to be somebody on the social networks.

Enterprise mobile vendors must now add to their portfolio's tools and APIs that will enable them to connect with and support social enterprise collaboration and social networking sites.  They must think beyond just delivering business process specific mobile apps, and now integrate with the larger social enterprise collaboration strategy and conversation happening in companies.

Read Part 1 of this series here.
Read Part 2 of this series here.

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Kevin Benedict, Head Analyst for SMAC, Cognizant

Read The Future of Work

Visit MobileEnterpriseStrategies.com

Follow me on Twitter @krbenedict

Join the Linkedin Group Strategic Enterprise Mobility

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