|By Kevin Benedict||
|December 10, 2013 12:15 PM EST||
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 that 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-p....
What is it going to take to eliminate blind spots and conjecture from your business?
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.
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