These days, the National Football League, BMW, and Uber have something in common — they’re all experimenting with big data in exciting new ways. The NFL is using big data to help football fans track how fast and how far their favorite players sprint during a game. BMW is using big data to help drivers anticipate upcoming traffic light changes, and determine whether they need to speed up or slow down to make the light. And Uber is using big data to predict where riders want to go even before they get into the car.
Big data is fundamentally changing the way we live and work – especially in today’s digital and hyper-connected world where data can come from so many different sources, including social media, transaction logs, e-mails, voice notes, multimedia, text documents, videos, websites, audio transcripts, stock trades, geo-spatial data, and weblogs. If properly harnessed, this data can be a veritable treasure trove of insights, enabling businesses to make informed decisions based on hard facts and metrics, rather than gut instincts or rough estimates.
Big Data, Small Businesses
Large global companies like Amazon and Netflix use big data to great effect – we all know that. But what about startups? Do they need to consider big data, and is it even feasible for them to do so?
Yes! Big data can help startups understand their markets, products, and customers better than ever. It can also uncover hidden opportunities for growth and success.
A few years ago, big data analytics and tools may have been out of the reach of startups, but today, they have become increasingly accessible and affordable. What’s more, startups, by virtue of their size and agility, are well-positioned to act on big data insights faster and more efficiently than their larger counterparts.
Going forward, big data is likely to become an essential part of business. A 2015 global survey conducted by Forbes Insights in association with Teradata found that 59 percent of executives consider big data and analytics either a top five issue, or the single most important way to achieve a competitive advantage. What’s more, two-thirds of executives report that big data and analytics initiatives have had a significant, measurable impact on revenue.
While the respondents of the survey were mostly from large organizations, the implications are similar for smaller businesses and startups. Big data can be a key differentiating factor, enabling businesses to strengthen performance and profitability. And the time to start mining, managing, and analyzing that data is now.
With that in mind, here are a few best practices for your startup to manage and derive the most value out of big data:
1. Identify the Challenges that Big Data Can Help Solve
Big data isn’t going to magically generate insights. The key is to start by asking the right questions. Do you want to acquire new customers? Do you want to make your operations more efficient? Do you want your sales strategies to be more targeted? Do you want to know how your business is faring vis-à-vis the competition?
Only when you identify the questions or challenges that you need to address and solve, will you be able to get the most out of big data analytics.
A few years ago, a leading Middle Eastern aluminum manufacturer approached MetricStream, wanting to know if they could effectively predict the risk of losses from events such as power outages, supply disruptions, and market price volatilities. Our answer was a resounding yes. Through a combination of analytics and statistical modeling tools, we helped the company run data-based and scenario-based simulations to calculate their value-at-risk in various loss situations, and examine the complete range of possible outcomes. With these insights, stakeholders were able to make more informed decisions about their risks.
The point is that there are plenty of tools out there, and there is no shortage of data which can be harnessed to provide insights that can help your business. However, unless you identify the top two or three areas that you want to address on priority, it will be hard to get off to a solid start.
2. Develop a Big Data Strategy
Many businesses tend to get swept up in the big data buzz – they launch ambitious IT projects to capture all kinds of raw data, only to end up struggling to sort through it with clarity and direction.
At the onset, create a strategy outlining how your
