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August 28, 2015

4 Tips on Outsourcing Big Data Analytics

Before we delve into the value of outsourcing big data analytics, let’s quickly consider what does it mean. Big data analytics refers to the process of studying big sets of data, intent on discovering patterns, correlations, customer preferences, trends, and so forth. Analysis of big data allows companies to make better business decisions. Some of these better business decisions may include more effective marketing strategies, new revenue streams, improved efficiency, better customer service, and new business opportunities.

Although a wealth of important insights can be garnered from big data, accessing these insights is challenging and typically lies beyond the scope of routine business intelligence. In fact, big data analytics is usually performed by data scientists who use statistical software and predictive models to sift through transaction data, social media, email, web server logs, survey responses, IoT, and so much more.

Some of the largest and most successful companies in the world–Starbucks, T-Mobile, and Walmart–rely on big data analytics. Many of these companies have the means and experience to organize their own teams of data scientists. However, with the great cost and steep learning curve associated with assembling an in-house team of data scientists, outsourcing big data analytics is a good idea for most small- and medium-sized companies. Furthermore, there is currently a dearth of capable data scientists out there which makes it even harder to find good full-time help.

Here are 4 tips to think about before you contract a third-party to help you analyze big data.

Tip 1: Try out your consultants

Please keep in mind that just because you hired on somebody to analyze your big data doesn’t mean that you’re stuck with them. When hiring consultants, find people who can help with your current projects rather than compel you to commit to long-term, cyclopean tasks. Ideally, you should first hope to see tangible results with smaller projects, and build trust this way.

Tip 2: Protect your data

Anybody who analyzes your big data needs access to information behind your firewall or in your cloud. However, it’s a good idea to be smart and secure about how you provide this data. For example, provide customer information without identifiers like names. Imagine how terrible it would be if your customer data was somehow linked to competitors or the general public!

Tip 3: Understand the analysis

Sure, some of the results from big data analytics may be quite technical. However, you should do your best to understand outcomes as well as you can. Consider assembling your own in-house team to act on the analysis. Remember that in the end, strategic decisions are within your purview and shouldn’t be delegated to a hired gun, no matter how good that hired gun may be.

Tip 4: Understand your alternatives

McKinsey & Company and BCG are two superstar consultancy firms to meet your big data needs. However, stellar consultants often come with astronomical price tags. If you’re on a budget, you may want to consider one of the several other companies out there that analyze big data–many of which can be found outside of the United States and Europe. Just be sure to thoroughly vet whomever you choose.

Ultimately, when hiring a third-party consultancy firm to help you with your big data needs remember to be thorough, be careful, and own the process and results. Analyzing your big data can definitely be a boon for business, but only if it’s done right.