Tag: mobile data capture

Enterprise Mobility Exchange – Post Event Report

Enterprise Mobility Exchange just hosted its East Coast edition of the 2017 Transformation Exchange which took place in Braselton, Georgia. I’ve just downloaded the post-event report which is available on their website . Among the findings:

Enterprise mobility is rapidly evolving causing the industry to face more diverse challenges than ever before. Think IoT. According to a survey completed by the event attendees 54 % will be investing in IoT software over the coming months and 48% will be investing in IoT hardware.

Security is of course a major topic for concern. How can security be maximized without inhibiting functionality, collaboration and innovation? 73% of event attendees will be investing in application security.

Of most interest to me, at this particular point in time, was the apparent debate over the methodology for developing and deploying mobile apps. Not up for debate – business users want their mobile apps and they want them now!

The traditional approach to mobile app development is not working any longer. The process of design, development, integration, QA, deployment, user testing, change management and finally user adoption could take months and easily run over budget. And that’s only for one application!  Mobile app development must scale to the needs of the enterprise.

Mi-Corporation is in complete agreement with the business users, we too want them to get their apps, and get them now. Why should they, or anyone in an organization, have to wait to become more efficient, or better utilize their valuable time, or gain access to captured data for analysis or reporting? (A mere sampling of the benefits associated with a mobile data capture solution).   Over the coming weeks we will be sharing some exciting news regarding this topic – stay tuned to learn about our new solution for empowering citizen developers, business users and the mobile workforce alike!

International Livestock Identification Association

I had the pleasure of attending the International Livestock Identification Association (ILIA) conference last week hosted in Boise, ID. The event was one of the best conferences I attended in decades and the folks who facilitated it brought a long list of A+ rated industry expert speakers, and also did an excellent job of fundraising for youth educational scholarships. I would also add that these passionate professionals of Agriculture and Livestock are as close to one another as any family can be.

If you are part of the Agricultural eco system, one topic that is on everyone’s agenda, is the challenge to build out a nationwide traceability system for the movement of livestock. This is no small task as you can imagine.  Each state having its’ own regulations, heavily influenced by federal guidelines, and usually running into obstacles when it comes to gathering support.

Imagine you are the producer, perhaps beef or dairy. Your take on what type of regulations are needed is different from the sale yard, which differs from the slaughterhouse and packing facilities. A couple of common elements that rang true through the conference:

  • Nobody wants more regulations and those who see the wisdom in having them do not always agree on the scope and are most concerned about oversight and regulatory enforcement.
  • No matter what else we do in the future, adopting a livestock movement and traceability system will be impossible without deploying new technology.

I’ve learned over the past two years working with our agriculture clients that livestock is as mobile of an asset as you can imagine. From the time of birth to end of life, all livestock, especially cows, are mobile. Whether it is within the confines of the ranch, to the feedlots, to the sale yard, to a new home on the range, they live a life of mobility, sometimes on foot, other times in trailers or trucks.

If your mission includes tracking mobile assets, you had better have a robust mobile data platform to do it.  Mobile Apps have become commonplace in many businesses to gain efficiency, improve safety, enhance worker productivity, control costs, and effectively capture and communicate data with 100% accuracy from outside the building to back office repositories for reporting and analytics. In the many years of consulting, designing and deploying mobile systems, the need for technology has never been so apparent than applying it to support this nation’s livestock movement and disease traceability endeavor.

For a solution to be successful in the livestock traceability, it will need to be extremely easy to use and as adaptable as the day is long. The users include a wide range of profiles, e.g., ranchers, truckers, veterinarians, meat facilities, brand inspectors, law enforcement, and anyone who produces or needs to register livestock product.

Consistent with the messages delivered at ILIA this year, it’s clear that any mobile data capture solutions put in place will need to be compatible with the latest input technologies to function at the speed of commerce. Those include:

  • Cameras
  • RFID
  • Microchips
  • GPS
  • Other premise-based technologies

In the case of environments like feedlots, farms or sale yards, standard keyboard input is typically not a preferred method of data input.  Therefore, mobile apps also need to support pen stylus for handwriting recognition, quick pick drop down for standard entries, and voice to text for speed of narrative notes by inspectors in the field.  An effective system will depend on the asset (livestock) being uniquely identified in some manner and the identifier will need to be read at the speed of commerce to support high production areas for traceability, such as a sale yard where hundreds or thousands of animals may arrive and depart like travelers through JFK.

This new frontier offers many opportunities to improve safety, quality of product, reduce theft, and most importantly, reduce the risk of disease outbreak and spread.  The challenge is not just finding the right products, but also finding the right partners to help design and implement these solutions in harsh environments with something less than a willing user community (and I’m not talking about the cows here!).

Finding the right mobile data collection partner is critical to the success of such a demanding environment.  Deploying a solution that is adaptive, effective, and easy to use will be the keys to success for the nationwide livestock and disease traceability infrastructure.

 

 

Using Inspection Data for Predictive Analytics (Believe the hype!)

One of our first customer champions, Dr. Etta Pisano, a nationally renowned Breast Cancer Imaging Radiologist with Harvard Medical School, recently shared a TechRepublic article on Facebook that probes the question—is machine learning overhyped?

My answer is a definitive no. As a computer scientist, I’ve spent many years studying machine learning and its practical applications. And while I believe that certain applications of machine learning are overhyped, in general machine learning is not overhyped at all. In fact, machine learning is worthy of its hype—and we’ve only started to scratch the surface of its potential.

Take, for example, speech recognition. In the early 1990s, I saw moderately accurate speech recognition software with a somewhat limited vocabulary on very powerful Unix workstations. At that time, the technology seemed impressive—but it had a long road to successful commercialization.

Today, we have great speech recognition in the cloud through our Smartphones, which I use every day for emailing and texting. Powerful machine learning algorithms are only possible with ample amounts of training data. We have more capacity than ever to capture, store and compute models based on very large amounts of training data. Every Google and Apple speech recognition user is supplying training data to those companies, if they give permission—and in doing so, we’re helping to create a more intelligent product for everyone.

So how does this apply to your business?

Machine learning, and practically speaking, predictive analytics, is starting to impact the inspection management market in many ways. One Predictive Solutions eBook discussing workplace OSHA safety put some of the traditional (non-predictive) practices in perspective:

“…waiting for incidents to occur before preventing new ones sends a very chilling message to employees about the company’s safety culture. To put it bluntly, leaders are essentially saying, ‘Joe, I am going to wait until your arm gets severed in our production line before I figure out how to ensure Susan doesn’t suffer the same fate. In the meantime, stay safe, and keep that production line moving…we have profit goals to hit.’ If leaders are trying to drive both a strong safety culture as well as productivity, this is not an acceptable option.”

Many industries (a few examples below) are now using their inspection data points to predict business-critical incidents and deliver huge benefits such as:

  • Fewer overall incidents
  • Increased public safety and improved health
  • Time savings
  • Cost savings
  • Increased productivity.

Superior data accuracy provided by the Mobile Impact Platform mobile data capture system is critical to creating and utilizing effective predictive analytics solutions.

Elevator Inspections

A page from Harvard’s Data Smart City Solutions discusses various use cases for predictive analytics. It’s focused on different US cities’ use cases, and it’s a nice reference if you ever want to learn how various types of operational challenges can be tackled using advanced data and analysis techniques. One interesting use case that we’ve been looking at for a while now is elevator Inspections. Harvard poses the question: “How can we prioritize annual elevator safety inspections? For example, can we predict or identify which elevators pass every year…?”

Workplace OSHA Safety Inspections

The Predictive Analytics eBook I referenced above provides some very interesting insights into the practice of using inspection data to predict—and prevent—future workplace incidents. The eBook discusses four “safety truths” that can reduce workplace injuries including doing MORE inspections (thus acquiring more predictive data points), hiring more (and more diverse) inspectors to do the job, and recognizing that worksites deemed either 100% safe or at the greatest risk can BOTH be the strongest candidates for future liability. The safety truths were derived from over 100 million safety observations and nearly 40,000 safety incidents, an ample amount of training data.

Food Inspection

The quality and safety of the food we serve (and eat) in the United States is important to us all. The city of Chicago has tackled this critical public health challenge handily—with the employment of just three dozen inspectors responsible for 15,000 food establishments and the power of predictive analytics.

This Government Technology article discusses a pilot program that yielded striking results. When using an advanced analytics-based procedure, Chicago data scientists discovered critical food safety violations, on average, seven days earlier than when traditional inspection procedures were used. The results have implications not only for Chicago but for forward-thinking cities everywhere that see the value of using advanced predictive analytics.

In summary, machine learning and predictive analytics are far from overhyped—in fact, we’re just getting started. In today’s world of immediate gratification and “google me” results (a luxury I appreciate just as much as the next person), sometimes people forget that collecting and actualizing the use of good data is often a marathon and it’s never a sprint. I’m personally excited to explore what we’ll be doing next and how Mi-Corporation can help shape the future of predictive analytics for our customers. I can’t think of a single customer we have today that wouldn’t benefit from predictive modeling tools. When they’re properly applied and expertly interpreted, incredible insights (and huge business benefits) await.

Stay tuned!