Month: January 2014

Google is flush with data. It collects millions of interactions each day, from people trying to find the best healthcare insurance to those just looking for a decent bite to eat. It stands to reason, then, that the company would use some of those capabilities to help its own internal processes. 

Among the most important of those is hiring. Having the right employees is a critical part of effectively realizing your goals, and that starts with the candidate identification process. In Google's case, analytics helped the company identify that the most valuable candidates don't always come from traditional recruitment channels.

Once they were in the interviewing stage, Big Data still proved helpful. One of the major takeaways from their research was that rather than asking a series of random hypothetical questions, it was more important to figure out the behavioral trends of the person being considered. Curating questions that got to the real core of how a person is likely to adjust to a scenario was a much more valuable selection tool than simply asking, "what is your biggest weakness?"

Finally, Big Data helped in the actual hiring. In a company of that size, it can be very difficult to maintain a strongly unified company culture. By ceding some of the guesswork involved to analytics, Google is able to better pick out who will fit in. 

The same principles could very well apply to a company smaller than Google. FileMaker support could revolutionize the way you make hires, and help to mold a staff that fits well into the culture of your company and does reliably excellent work. 

In the past, health care was completely responsive. A patient would come in with a particular malady, a doctor would diagnose it as best as possible, and then they would set out on a course of treatment. Now, physicians are making a greater attempt to anticipate and react to health related issues, before they even rise to the level of requiring a clinical visit. 

For many doctors, Big Data can be an important part of those efforts. One of the primary issues in modern health administration is the sheer amount of infrastructure and scheduling necessary. Unlike the past, when a house visit could be made on a particular day, modern medicine necessitates a level of administration that can often be cumbersome. That is where analytics can come in. 

One of the problems that doctors face is coordinating records across multiple systems. Many things are done on paper and have to be scanned or filed by hand. By using the FileMaker service, however, they can better organize data and treat patients more effectively. 

There are ancillary benefits as well. By parsing the information and identifying trends, a physician can see which patients are likely to come back and how often, knowledge which can speed up their care process. In addition, they can pinpoint factors that are leading to recurrences, and note national health patterns before they reach the level of crises. It could even reduce the incidence of chronic diseases like diabetes and cancer, which tend to occur relatively more frequently in particular populations. 

As care gets more specialized, it will be fascinating to watch how doctors are able to implement new database technology into the age-old process of making people feel better. 

In this space, we've discussed how Big Data principles can help you make better hiring decisions. Now, with the right database and some shrewd analysis, it can help you determine which employees deserve to be promoted — and which ones should be shown the door. 

It's difficult, bordering on impossible, for any manager to be completely objective about his or her staff. You get to know certain people better than others. Some employees are great at appearing to put in a lot of effort without actually trying very hard, and others have a difficult time promoting the good things they are able to do. 

In a big company, with a huge staff, these sort of imbalances even themselves out over the course of time. Even if the promotion/firing process isn't as efficient as it could be, the sheer size of the business serves as some insulation against a few less-than-productive members. For a small or medium sized business, however, every employee is a vital cog in the machinery that keeps things moving forward. If one isn't working properly, it's time to make a switch. 

That's where FileMaker support can help. 

Instead of being forced to simply use the eye test and determine which employees seem to be the most capable, you can actually create a database that will identify the metrics most accurately correlated with success. The results could end up surprising you: criteria that seemed negligible may in the end wind up being big drivers of sales. In addition, a more data-driven promotion process will more accurately reward the best employees, and allow you to cut yourself free of ones that are hampering productivity. 

Attached are the zip files for the FileMaker 13 certification Exam Review. These files were used in both the CFDG and BAFDA meetings. Please feel free to study these as needed when getting ready for the FileMaker certification test. If their are any further questions please feel free to contact Tim Neudecker at tim@kyologic.com

Files: Certification Part 1_0

A strong company starts with the right employees. If the people carrying out your strategies aren't talented and capable, it won't matter how worthwhile your vision is. Thus, being able to hire well should be a priority for any business. By identifying and retaining the best possible candidates, you can put your company into a position to thrive. 

It's a process that could benefit from FileMaker help. 

Hiring is by its nature an inexact science. Not only do you need to evaluate a person's skills in a short period of time, usually on the basis of nothing more than a resume and a handful of brief interviews, you also need to envision how they fit in with your corporate culture. Somebody who is perfectly suited for the role might not fit in with the rest of the staff. If this is the case, you've wasted your time and prevented yourself from having the best possible team.

This is where analytics come in. Parsing data on your current employees, as well as on the candidates you are looking for, can help you decide what metrics are actually important for a particular job. The answers could very well be surprising. Building the right database can even give you a way to incorporate information that would otherwise be tricky to mesh. In a recent article on Wired, author Michael Morrell discussed these sorts of criteria.

"Remember that personal interaction and communication provide perhaps more important data than massive amounts of publicly available data. Did a candidate respond to an email? Show up for an interview? And of course there are the personal referrals and references, which should carry a lot of weight in a matching algorithm," writes Morrell.

In addition, a stronger adherence to big data processes in hiring will benefit job seekers. Potentially talented people who have had issues showing it will be evaluated more holistically, which can take some of the pressure off of resumes and cover letters, both inexact proxies for actual talent. If hired, they will also be much more likely to fit in well with the company, since they would have been selected for traits that make that a likelihood. 

It's a win-win: businesses get the best possible staff, and candidates find the best possible working situation. 

Residents across the Northeastern part of the United States, from Ohio to Maine, are in the process of digging out from the first major snow storm of 2014. Some areas have seen as much as two feet of the white fluff pile up and keeping the roadways clear is becoming increasingly difficult. On top of that, the below-zero temperatures are making road treatment processes less than effective.

This scene is not unusual in many parts of the United States during the winter months, but there is a new innovation that is making snow removal and road work much easier.

A recent article from the Daily Camera, a Boulder Colorado newspaper, profiled the National Center for Atmospheric Research (NCAR) and the new "smart plow" it developed and is testing in Michigan, Minnesota and Nevada. The process works by analyzing information from several databases including satellite and radar observations, computer weather models and real-time data collected from special sensors outfitted to plows that are clearing the streets.

The goal is to continuously monitor weather conditions and keep up with trouble areas more effectively. This will reduce accidents and save states potentially millions of dollars in maintenance.

"Whereas in the past, drivers would have some new data maybe every 30, 40 or 50 miles, now you could just look up every mile, and hopefully pick up the more subtle small things that happen on the roadway," said Sheldon Drobot, the NCAR scientist who has overseen the system's design.

This is just another example of how custom database software can be used to harness big data and improve an aspect of daily life.