Today there are a few buzzwords that get tossed around a lot in the business sphere. Chief among them is “big data.” In fact, big data can be read about in almost any sphere. Big data, as defined by sas.com, is the recent growth and availability of structured and unstructured data. Traditionally in business data is looked at from a marketing perspective. Collecting data on consumers and purchase patterns allows for marketing teams to more precisely target valid perspective customers with the right ads at the right time.
However, big data is not only limited to marketing applications. In an article featured in Forbes, Vince Dell’Anno notes that companies need to be looking for ways that big data can benefit their entire organizations, not just one aspect. One key benefit of big data is using it to boost productivity throughout your business, here are a few ways you can use big data to this end.
Use big data to expedite and improve upon the daily procedures of your business. Have employees keep track of what they are doing, when they are doing it, and how long it takes. Build a log of this information and search for patterns. Are there ways that could make day to day tasks run more smoothly? For example, a study done by the International Institute for Analytics and the SAS institute show how UPS was able to incur huge savings through big data analysis. UPS collected data on their trucks speed, performance, braking, and direction. They used this data to measure performance, but also re-configure the routes driven by trucks during deliveries. In doing this, they cut 85 million miles off daily routes and saved 8 million gallons in fuel. Estimating that a cut in 1 mile per driver saves $30 million, the monetary savings were significant. At that, UPS has begun using big data analytics to optimize their aircraft deliveries as well.
If you are without a team of analysts, you may consider a third party software that can log the data that is relevant to you to give you a more accurate readings on productivity. The Harvard Business Review notes in its article “Big Data: The Management Revolution,” that many airlines have done this by partnering with PASSUR Aerospace. PASSUR finds data relating to weather, flight schedules, and local airplanes to give more accurate flight ETAs. This saves the airlines time, money, and angry tweets from passengers sitting on runways. Again, big data has demonstrated its benefits beyond marketing strategies, benefiting the organizations as a whole.
Big data can also help productivity on a more individual level. In her Time Magazine article, Lauren Simonds contends that having a greater understanding of your employees through big data will give you a better knowledge of how they will perform. Proximity to the office, number of social media sites in use, field reps vs in-office reps, etc. all give different insights into how productive an employee will be and how long they are likely to stay at a job. It has also been found that employees are more likely to check in on their own performance if they can do it online. Jeremy Boudinet notes that people will always prefer checking Google Analytics, or another data collection medium to see their current numbers to having a sit down with their boss. Citing this Harvard Business Review article, which notes that employee ratings conducted by managers are often misguided, Boudinet also notes that using big data to remove bias from employee ratings will garner higher employee engagement. So not only can big data benefit your business operations, it can also benefit your employees productivity individually by tracking their progress digitally and concretely for them to review.
Big data is everywhere and it can benefit almost every facet of your business. it can be leveraged to increase overall productivity, and employee productivity on an individual level. Log information about day to day tasks and employee stats. If there are any patterns, see how you can improve them or leverage them. Can you use big data analytics to improve your company structure and productivity?
