Written by Devin Pickell
It’s on your Twitter feed, your LinkedIn connections are sharing articles, and just about every tech publication has it in their headlines. I’m talking about big data, and there’s actually a good reason for all the hype.
Big data is seriously big. By 2025, there will be 163 zettabytes of data generated throughout the world. Wait Devin, what’s a zettabyte? One of them could store 2 billion years worth of music. Multiply that by 163, and that’s just enough music to get you through a long work week.
But big data is also fast. So fast, that there are 510,000 comments posted, 293,000 statuses updated, and 136,000 photos uploaded to Facebook every minute! That’s a lot of personal data.
There are many varieties of data in the digital universe as well. Video content, voicemails, emails, text messages, tweets, and many other forms of data can be generated in the palm of our hands. This wasn’t a reality just over a decade ago.
There’s your snapshot of big data, but what is its actual purpose? When harnessed properly, big data can help us achieve many things – especially as analytical platforms become better equipped for such large volumes of data.
In regards to future workplaces, the use cases of big data only expand. Here are 4 ways big data will have some sort of impact:
1. Big data and CRM
Today’s customer relationship management (CRM) software does a great job at providing many departments within a business with an overview of their customers and where they’re at along the lifecycle. Data from CRM software can be used to personalize sales processes, target marketing campaigns, nurture customer relationships, and more. So where can big data innovate CRM?
CRM software works particularly well with structured data, such as demographic information like names, product history, addresses, and other identifiers acquired from leads. Big data, however, consists of mostly unstructured data, such as sentiment analysis from social media networks.
While structured data fits neatly in a database and can be quickly pulled for analysis, this isn’t the case for unstructured data – which is much more diverse and seemingly random at times.
The benefit of integrating unstructured big data in your CRM system means deeper insight into your customers, and uncovering patterns and trends that may not have been present before. Deeper insight can lead to predictive modelling, better customer segmentation, innovative customer experiences, and avenues for new product offerings.
Image courtesy of Carlos Muza
But integrating big data into CRM systems is quite the task. Not all data is of good quality or even relevant to a businesses’ bottom line, so data cleansing would be needed to find the right data. Right now, this is an expensive process that not many organizations can afford.
2. Big data and hiring
Paper resumes have evolved into one-click digital contact forms, and there are more ways to apply for a job than ever before. While this is great for generating a deep pool of potential talent, not all applicants are cut out for the job. This means your HR staff will have to sift through mountains of resumes before those initial interviews, or rely on job portals to parse keywords on resumes – a process with a 2-4 percent effectiveness rate.
A hire is made, and after months of onboarding, the selected candidate doesn’t work out. You’re back to square one. The estimated cost of this bad hire is up to 30 percent of their first-year earnings, according to the U.S. Department of Labor.
Thankfully, smarter hiring practices are on the horizon through the use of big data analytics paired with artificial intelligence (AI) and machine learning.
Large volumes and varieties of data on potential candidates can be fed into a neural network for deep analysis on everything from personal traits to cognitive abilities. Big data analytics can uncover which factors lead to a successful hire versus a failed hired. AI can also mine data from current employees to set benchmarks and better define the roles of future candidates.
While the algorithms used to build these programs will need consistent testing, big data can take a considerable load off of HR staffs. This will lead to increased productivity, better employee retention, and reduced resources towards finding the right candidate.
3. Big data and decision-making
You know the saying, “work smarter, not harder.” In the age of data-driven businesses, working smarter through the use of data analytics gives you the competitive edge. Research firm IDC estimates that organizations that make it a priority to discover and analyze relevant data could generate an extra $430 billion in productivity by 2020.
Big data analytics will only help businesses make smarter decisions faster – allowing them find disruptive opportunities the moment they arise. Of course, this means harnessing real-time data streams, which requires a level of discerning good quality data from poor quality data.
4. Big data and office spaces
So far we’ve discussed how big data can contribute towards smarter hiring practices, deeper analytics, and more personalized customer experiences, but did you know that big data can also have an impact on your office space?
Thanks to big data and its main driver, the internet of things (IoT), smart connected devices can lead to more efficient and innovative office spaces.
Facility optimization is one way IoT can be be used to save energy. Embedded sensors at key areas throughout the office can detect which parts of the building are commonly used at which times of the day. Electrical components can be automated to power on or power off when necessary.
Image courtesy of Ixoria Technologies
Sensors outside the building can obtain real-time weather analytics to adjust for changes in temperature – prompting the AC or the heat to kick in. How cool is that?
Predictive maintenance is another trending use of big data and IoT. When areas of the building aren’t performing at their optimum levels, sensors could trigger these responses, and AI/ML will notify building administrators the root cause of each problem before any costly damage occurs.
With only 0.5 percent of the world’s data analyzed and ready to be applied, we still have a while to go before things like big data, IoT, AI, and machine learning have an everyday impact on our lives. But big data isn’t inherently valuable, and without applying it towards a problem or a goal, big data doesn’t serve much purpose.
As the digital universe continues to expand, businesses will focus less on acquiring massive volumes of data, and focus more on discovering relevant data. Before data can applied, it’s important to have a firm understanding of the business objectives you’re trying to reach with the support of big data.
Devin is a Content Marketing Specialist at G2 Crowd, generating content for its Learning Hub. He has experience marketing for early-stage startups out of Chicago’s booming tech community.