“An organization’s ability to learn and translate that learning into action rapidly is the ultimate competitive advantage.”
– Jack Welch (Former CEO of General Electric)
These words have never been apter than they are today. The term ‘Big Data’ gets thrown around a lot, with a horde of services created to collect tons of data for you. Exabytes of data get collected each day from a sea of user website clicks, increasingly driving more efficient algorithms to cater to growing business needs.
There is not a single industry – big or small, old or new, digital or industrial, that has not tried to use it to transform their services and advance their business strategies. However, in today’s world, the largest hurdle towards deriving value from the data is not its sheer volume but further analysis of it. Big data in itself is not of any use if one is unable to derive valuable insights from it.
It’s not about the volume
Successful businesses realize the importance of pursuing the right data, and not just relentlessly focus on volume over value. Let’s elucidate the data success story of Uber.
At a time when the availability of taxis was not linked to the internet, a taxi could only be summoned by a visual show of hands. Uber’s elegant solution to this was to stop running around on the basis of visual data — and muster the right data to get the job done. Creating an app, which runs on the handsets of both the drivers and the customers, Uber managed to generate a huge wealth of data which allowed it to map the real-time logistics flow of human transportation. But Uber’s success doesn’t come from the huge amount of data it collects; it is rooted in its ability tap into the right kind of data.
While harnessing the power of big data allowed Uber to enter larger markets globally, the right kind of data enabled it to create an elegant solution to the ever-growing transportation needs of public – dispatch cabs in real time.
Getting the right kind of data for the job
At times, substantial data can be humongous, and at other times it can be small. To innovate, it is essential to find the right kind of data which can give you a competitive edge over rival businesses as well as cater to the basic purpose of your organization. Hunting down such data can be a tedious task. To help you find a needle in the haystack, here are a few questions to keep in mind:
- The Decisions that’ll drive waste into your business
Waste management is a greater problem than anticipated for a large number of businesses. But the right data can make a business disruptive by eliminating waste entirely. As Harvard Business School’s Ben Edelman rightly quoted, “waste makes for opportunity.”
It can be industrial production, retailing or legal investigations, finding out your sources of wasted effort and resources can guide the way towards right data. It can be as simple as identifying predictions, like how much inventory to stock. Charting out these decisions point towards sources of waste, which can increase the benefits gained from the right kind of big data.
- Which decisions can be automated to reduce waste?
Humans are great at making certain types of decision. When it comes to deciding the optimum advertising campaigns, marketing strategies, and branding, humans can be brilliant. But when it comes to making simple, repetitive and operational decisions, machines tend to fare better.
For instance, Amazon is rumored to have eliminated almost all of its pricing team, replacing it with algorithmic control. A strategy most retailer would be apprehensive to follow. But if Amazon’s algorithm works, it would mean that far less is being spent on discounts, on inventory pileup and better predictability of new product introduction, each of these would give enormous competitive advantages.
- What data is required to do so?
Once you have garnered a deeper understanding of the waste in your legacy system and the decisions have been charted, the last step is finding out that if you could get your hands on any piece of info, what would it be?
In Uber’s case, to automate the decisions, they needed to know exactly where all the riders in the city were. Whereas, in the case of General Electric’s Prix Industrial Internet Software, the company wanted to know exactly when a machine was going to break down by automating maintenance decisions. These are the right piece of data you need to seek out to further your business. Many companies simply spend too much time collecting huge amounts of data and not enough time to seek out what the right data is.
One way to avoid getting lost while sifting through mountains of data is to focus on market research and capture only that data which can help provide meaningful insights and findings. This information can be garnered in various forms, like:
- Business profiling
- Case studies
- Organizational structure and reporting relationships
- Products and services that relate to your business and your market
- Evaluation of competitive products and their services
- Pain points and wish lists
- Key decision makers and influencers
- Customer satisfaction statistics
Looking to sort out your big data queries? Contact Datahut for efficient solutions.