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Is Your Data Too Big For You? Assess Whether Your Big Data Needs Help

Posted by Phil Van Wormer on Apr 21, 2015 9:29:39 AM

th-5In their 2015 ProMat presentation, Big Data for Your DC, TotalTrax partner, Swisslog, made interesting and critical points about the complexities of big data. The amount of information spreading around the world can be overwhelming, reaching numbers that make it hard to wrap one's mind around them. According to research firm Gartner, "approximately 3.9 billion connected things were in use in 2014 and this figure is expected to rise to 25 billion by 2020." Connected devices and people provide data, often in the form of "unstructured data coming from sources such as text, voice, and video." According to IBM 75% of data is unstructured. With your storage of traditional, historical data and this new, unstructured data, have you asked yourself who is going to handle this huge pool of information for your company?

Big data has helped many companies flourish, improving efficiency, investments, resource-management, basic decision-making, and profits. Harvard Business Review named Data Scientist the sexiest job in the 21st Century, but some people see this as hype. According to an interview in the Wall Street Journal with OK Cupid founder, Christian Rudder, “data science is something that an intelligent mathematical person who can program, who understands human nature and statistics, can do. It’s not like it takes a special genius.” Given the influx of data collection and mining, it could be critical to see which side you fall on. When thinking about big data and your company, here are some questions to ask:

Are we collecting and using the most important data?

Are you accessing the data you need and are you using it in the most beneficial way? It’s one thing to be able to read, but can you comprehend what you’re reading? According to the company VoltDB, “the 2014 Big Data Survey reveals that most organizations cannot access, let alone utilize, the vast majority of the data they collect, and exposes a major Big Data divide: the ability to successfully capture and store huge amounts of data is not translating to improved bottom-line business benefits.” Also ask: when we have the data, do we know which actions to take to capitalize on it?

Are we ready for a data scientist?

Knowing how a data scientist will fit into your current reporting structure is important. Will your current IT infrastructure support their needs? Data scientists can be pricy because they’re in high demand. Retaining employees is important, as it can be disruptive and expensive to lose them. Be certain that you have the plan, people, benefits, and tools to support a data scientist. In a market that is searching for these highly talented people, you want to ensure that if you secure one, they aren’t tempted away by another company.

Do we absolutely need to hire a data scientist to compete?

To answer this question you may need to ask several more questions. Harvard Business Review named Data Scientist the sexiest job in the 21st Century. Big data is abuzz in the business world. But do you need to hire one? Are the people currently handling your data producing helpful, action-based results? Like Rudder mentioned, if you have intelligent people who are talented in math, programming, statistics, and who has solid common sense, you should ask yourself if you need to implement change. Don’t hire a very expensive data scientist if you’re already getting the work done, or if you aren’t ready to support one.

Can we get training for current employees who analyze our data?

Assuming your current employees are already quite competent, yes! There are many online courses from reputable institutions, such as Johns Hopkins University, offering courses on data science. You can help bridge gaps current analysts might have, however some would argue that data scientists are specially trained and have knowledge and skills that can be hard to find, which is why there is a such a dearth of data scientists. You’ll need to do a cost-benefit analysis to see if it’s better to invest time and resources in educating a current employee, or in hiring an already seasoned data scientist.

Asking critical questions now can help set you up for a better future. A McKinsey Global Institute report estimates that by 2018, “the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.” Let your competitors be part of the shortage, not you.







Topics: big data, supply chain analytics, best practices, ProMat2015

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