How your mobile workforce can be a goldmine for collecting and analysing big data.
There is no denying the many benefits of collecting data. From improving company productivity to forecasting and preventative actions, there are countless ways that data collection can improve operations. Data is only useful, however, if it can be harnessed properly to achieve its maximal potential. Picking the right data to analyze and report upon is paramount to utilizing the data effectively. This involves having a targeted goal of the data you want to collect and the value you plan to receive from it.
What is Big Data?
A recent Business Insider report stated, big data is most commonly defined as data sets that meet three attributes, known as the three “Vs”: volume, variety, and velocity. But there is something more to it. “I like to say there’s a fourth V: value,” says Kipp Jones, vice president of product at Skyhook Wireless, the company responsible for first introducing hybrid location positioning. In order for data to be meaningful at all, it needs to be captured and stored efficiently. Then someone has to manage the data, analyze it, and extract value from it. Data, big or not, doesn’t add up to anything worthwhile if it doesn’t have value to someone.
Mobile Devices and Big Data
Collecting data in the field has traditionally been recorded on paper. This leads to a high probability of error and the necessity of data re-entry. Field workers will sometimes try to limit the quantity and consequently the quality of the data they collect to reduce their administrative workload. Having to then hand this data over to the proper department to enter into an analytic system creates a major lag in the process of collecting data, to deriving any value from it.
To help manipulate big data, mobile devices are providing new tools to collect data and deliver insights. Acting as delivery mechanisms, mobile devices are put into the hands of frontline workers who rely on real time information to perform their daily operations. Mobile devices have become extremely valuable in collecting and consuming data and analytics. By performing predictive analysis where problems and patterns can be identified, they help companies with preventative maintenance and future decision making, putting the right data into the hands of the right people.
Companies are moving away from intuitive decision-making and becoming increasingly data driven. By infusing analytics into everything their employees touch, it is making this process easier in day to day operations. The use of mobile devices to collect data has also increased the prevalence of big data for small business, allowing for companies of any size to optimize data collection, enhance decision making abilities, and remain competitive against larger companies.
Big Data Analysis
IBM pointed to the changing trend of organisations previously having to rely on highly trained and highly paid data scientists to harness the power of analytics. Now mobile apps are helping to bring the power of analytics to smaller companies and into the hands of the average employee.
The goal of big data is to draw meaningful conclusions by gathering information from different sources. According to the Digital Innovation Gazette, about a decade ago, regulators such as the FCC began requiring all new mobile phones to have built-in location technology such as GPS to help find emergency callers. Those mandates were a milestone in big data history because they changed the nature of the information that can be captured and mined compared with desktops and laptops. “The big difference is that desktops are stationary and laptops do not in general have GPS sensors, so there is a location awareness in the data that can be captured and mined from a mobile device,” says Andrew Purtell, principal architect at Intel.
Big Data Solutions and Challenges
One of the biggest challenges in utilizing data and mobile devices isn’t the technology so much as it is the people. People that have been doing their job the same way for years are going to be resistant to change, especially if they have a piece of technology that is now telling them how to do their job better.
To become an organization that is data driven it has to come from the top. It has to be embedded in the culture that data analytics are a priority, and the organization is going to listen and respond to what the data is telling them. To get employees to buy into using analytics and their mobile devices, it has to be made apparent that the value that can be derived and the impact it has on making everyone’s job a little easier.