Using Artificial Intelligence in Health Services Requires Real-Time Enterprise Mobility

I am intrigued by the increasing use of artificial intelligence in areas like field services management and home healthcare services.  I read a use case (http://www.clicksoftware.com/Collateral/Documents/English-US/KinCare-Case-Study.pdf) this morning about KinCare and ClickSoftware in Australia.  KinCare provides all kinds of home and healthcare services across a wide geography in Australia.  They are one of the largest providers of in-home care and assistance in Australia and they get paid by providing documented services compliant with government regulations.  There are designated fees for each service and there are little to no margins for errors. It is very easy to screw up and to lose a lot of money in this kind of operation.

Let me provide an example of KinCare's services:

• Nursing care
• Personal care
• Domestic assistance
• Social support
• Respite care
• Transportation
• Case management

Some of their clients need all of these services.  These services are often provided by different people at different times.  Let's image tens of thousands of clients, care givers and service providers located all across Australia.  All of these participants and their appointments must be scheduled and coordinated.  Does that sound like a big enough challenge for you Mate?

The only way to run this kind of operation efficiently is to make sure the care givers and service providers are connected (via mobile devices) to an intelligent software system (using artificial intelligence and context aware systems) to understand how to most efficiently provide and schedule hundreds of thousands of services.  In addition, must also make sure each care and service provider is qualified, available and in close proximity.  Also it is important to note that these services are critical to a persons health and welfare.

The mobile devices are used as mobile data collection devices, sensors (GPS) and reporting systems in the service delivery process. Mobile devices feed real-time data to the real-time analytics and artificial intelligence systems that schedule all parties across the country.  Since all of these participants are mobile, it takes very careful and fast analytics to ensure all parties can meet in the right places, deliver and receive services efficiently, document services and invoice for those services.

Smartphones and tablets, broadband internet connectivity and ultra-fast artificial intelligence capabilities integrated with human resource, talent management, scheduling, case management, patient and service management, billing and dispatch systems are all required to make this work.  Wow!  Speed and artificial intelligence systems are revolutionizing these kinds of operations today.

When I am out teaching mobile and SMAC strategies to large companies the topics of speed, context aware and artificial intelligence comes up every time.  These are the game changers today.

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

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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.

Supporting GIS and Mapping Solutions on Muddy Tablets

J.D. Axford, P.E. CESCL

I want to introduce you to a long time friend of mine J.D. Axford.  He is a civil engineer with all kinds of acronyms after his name (P.E., CESCL, etc.), who has worked for most of his career in the Northwest of the USA in and around water and mud.  He is a hero among the duck population for his many years working with wetlands.  He is you may say, an expert in outdoor field data collection.

I can remember a time about 25 years ago when J.D. and myself were perched above a waterfall along the East Fork of the Lewis river in Washington state measuring water flow and collecting data together.  It was, in fact, cold and muddy work.

He shared with me recently the list of things he typically carries in his service backpack to collect data:

• bubble levels
• incline-ometers
• rangefinders
• GPS accurate enough to serve as an inspection-level pre-survey grade checker
• wet papers
• job reports
• field notes
• redline drawings
• change orders

He is a big fan of finding ways of reducing the items in his backpack by utilizing mobile apps.  In this article J.D. shares his insights on data, data collection, mobile devices, GIS and how they are all used in utilities work.

Collecting data is a big job.  Utilities both generate and demand tremendous amounts of data. They are designed and operated with the use of a lot of geospatial and asset data.  Maintenance and repair work generates data, which is of particular importance in predicting future staffing needs, maintenance costs, and for the management of risks. In the distribution side (in electrical utilities) data is generated that is used to predict economics parameters, consumer demand, and other trends essential to profitability.

A lot of data is also generated by field crews which come from tasks related to vegetation control, drainage and other similar items. This work and the data generated are of increasing importance as infrastructure ages and budgets tighten. The information must be captured accurately by field staff and uploaded to geospatial databases and document management systems and then be made available to all the stakeholders.

All of this data collection, especially the outdoor data collection, benefits from mobile devices. Think about the environment. Maintaining a utility grid requires working remotely, often in multiple locations per day and on a variety of different projects and issues.  A lot of data is collected in rugged, cold, damp and muddy locations.  In these environments, tablets are very useful as they are light-weight and offer the simultaneous ability to capture, store, query and process data.  Tablets can significantly reduce the time and effort needed to manage data if you can keep them from being damaged.

As important as tablets have become to many engineers and utilities, they still have limitations as memory is limited, the service environment can be harsh and connectivity lost. There is also the challenge related to different tablets using different operating systems.  Some GIS and mapping applications only support one operating system. Many of these limitations, however, can be solved by the right software.  Vendors like We-Do-IT of Australia have developed tablet-based GIS software solutions made to operate online and offline, on a wide variety of tablets and operating systems while integrating with most GIS and ERP systems.

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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

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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.

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

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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.

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. 

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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.