3 Ways to Use Big Data Intelligence to Gain Productivity
The concept of big data intelligence has been a buzz word of late. However, the exponential growth of data has transformed the concept of what big data even is. One thing is for certain – whether talking about data generally or big data - its value continues to grow and its importance is closely tied to what intelligence can be extracted from it. Computing devices are getting "smarter," the world continues to generate more of it (at an accelerating rate) and our lives are becoming more enriched because of it.
Data that just sits there doesn’t have much value. However, data that has been analyzed and can point to improved business performance is a different story. Once trends can be identified and conclusions drawn, future actions can be predicted to improve productivity. At that point, data transforms from being just information to becoming knowledge and wisdom.
Early Challenges of Big Data
Interestingly, the concept of “big data” was first seen as a problem to overcome. The volume of data being collected began to expand at a geometrically increasing rate, which then created big problems across an IT infrastructure. The concern quickly became how to handle the growth, and how to effectively access the data so it doesn’t get in the way of progress. Drivers of this problem included computer processing speed and larger hard drives, corporate networks supporting voice and data and the Internet. Fortunately, technology continued to advance, offering increasingly faster processing options to address these concerns.
Today, the value of data has grown considerably. It can be leveraged as a valuable resource to solve new problems. Data is now so valuable it is a target of theft! New software, predictive analytics and artificial intelligence are unlocking amazing opportunities to empower smart devices. This transformation is well underway in manufacturing. Other industries are following quickly. The manufacturing industry has made significant investments over the past decade to collect more data, analyze it and then leverage it for future performance gains. This information is being used to improve decision support, create smart factories and implement process improvement at levels not previously been possible.
Using Big Data Intelligence to Improve Productivity
Given all the data being collected, it makes sense that this information could be used to help improve sales and operations performance. When used effectively, data can help provide us with intelligence to work smarter with greater efficiency – these are not bad things!
Here are three examples that illustrate my point.
- Managing Deliveries & Logistics – here is an example of what happens when a company really understands its business, and is 100% devoted to being the best at it. According to UPS, they delivered 4.9 billion packages and documents to 220+ countries and territories in 2016. This feat was accomplished with 434,000 employees operating a fleet of over 100,000 vehicles (source). Wow!UPS consumes an enormous amount of data, including how to avoid wasting time. For example, if you track a UPS truck during any given day, you will notice that the driver avoids left turns. There are several reasons why. To start, left turns are not as safe. According to the National Highway Traffic Safety Administration (NHTSA), left turns cause 53.1% of cross-path crashes. Another reason is the fact that they waste a lot of time, which contributes to burning extra fuel. This strategy alone is estimated to save UPS over 98 million hours per year of idling – just imagine what the fuel cost savings might be on that metric alone!
- Managing Capital Expenditures – eBay has about 167 million active global users (as of January 2017) that bought a total of $84 billion of merchandise and generated about $9 billion of revenue in 2016 (source). At one point, eBay had 1 billion items listed for sale. As you might imagine, their IT infrastructure is significant. Naturally, eBay got serious about understanding how to improve their user experience by avoiding downtime and making smart capital investments.eBay began capturing “detail-by-detail, minute-by-minute” data on every component installed on its data centers. After analyzing this data, eBay uncovered underutilized servers, mis-configured devices and other inefficiencies. This intelligence suggested new strategies on how to utilize their servers, resulting in the saving of millions of dollars in capital expenditures within the first year.
- Managing Remote Sales Teams – Large companies such as UPS and eBay certainly have significant operations. Finding a small process improvement could easily translate into big cost savings. However, smaller companies can achieve great benefits too – some that extend beyond the P&L. Take Prodoscore as an example of a younger, smaller company that is empowering sales managers to better understand how their sales team spends their time during the day. This data is being used to compare sales performance between the team to unlock and validate new best-practices. In this case, we have a great example of "eating one's own dog food," in marketing speak.It is one thing to say how you spent your time based on what you recall – it is yet another if your activities were captured and quantified with data to then portray an accurate picture of how time was really spent. Comparing this data with quota attainment can yield very interesting conclusions and business intelligence. Similarly, discussion topics can be revealed through keyword searches to see if messaging is on topic and relevant, offering another way for process improvement. This type of process improvement could make the difference between survival or not, which is just as valuable as the cost savings that large companies can generate.
The collection and processing of data has now become a standard within business operations - regardless the size of your organization. You can’t compete if you are not embracing a digital business strategy today. And, as part of that strategy, you better take advantage of data collection, processing and analysis. The resulting big data intelligence can not only provide better productivity, efficiency and cost savings, but could be the difference between those companies that survive and those that don't.