Before Starting, Consider 5 Reasons Your Big Data Project Will Fail

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Whether companies are finding revolutionary ways to use data for personalized recommendations, like Netflix, or getting in trouble for illegally targeting users, like Facebook, big data is an integral element in optimizing efficiency. However, if your company is ready to give their customers a better user experience while shopping for the best homeowners insurance, or if you’re trying to save money in customer clothing returns, diving into a big data project isn’t going to be your saving grace.

In fact, according to Nick Heudecker, an Gartner analyst, 85 percent of all big data projects fail. These failures come from the lack of understanding in how to run a big data project, and in an interview with interview with TechRepublic, Heudecker sites company adoption as the sore spot, not the technology itself.

If your company is itching to use data in their business practice and wants the project to succeed, there are simple steps to help you stay out of the 85 percent statistic. We’re detailing the 5 mistakes you are likely to make during your big data project that would make it fail in hopes that you can avoid these problems before they arise.

1. You aren’t open to the answers you’ll get

As Heudecker stated earlier, big data projects don’t fail because of the technology. They are more likely to fail due to difficulty fitting into the current workflow and being accepted by higher-ups. This is confirmed by a survey conducted by the Fortune Knowledge Group which finds these powerful executives more likely to “trust their gut” over the answers data projects derive.

A survey conducted by NewVantage Partners on big data adoption finds that failure “lies in the apparent difficulty of organizational and cultural change around big data. Big data technology is not the problem; management understanding, organizational alignment, and general organizational resistance are the culprits. If only people were as malleable as data.”

When beginning any new project or adopting a new technology at work, it is difficult for seamless integration to start at the bottom. If higher up executives are truly on board with the effort, a company adoption will benefit from their outright confidence and practice of the technology. This not only sets a precedent for the other employees but allows for faster and smoother integration into the workflow.

2. Your goals aren’t clearly defined

If your higher-ups aren’t completely on board with big data or don’t understand the value big data can bring to a company, this can create an adoption problem. Begin your efforts with a defined goal that is measurable and shared with others. Simply to ‘improve efficiency’ or ‘enhance the customer experience’ are not measurable or sharable. If you want to save money for your retail company, look at ways to decrease customer returns. If you want to generate higher revenue, look at ways increase sales through your affiliate links.

Not only can these elements be tracked and presented, but it puts your team on the same page. Big data is called big for a reason—there’s plenty of it. Your team can get easily overwhelmed if you’re not working towards a concrete marker that can be a marker for success.

3. You’re working with too many people

When coming from a place where big data is contested, if you start with a large team that doesn’t produce immediate results, this could discourage your company from continuing with the project. Start with a small team of essential people and define your goals for success. Once the project gains momentum and the results of your efforts and integrating into the workflow, you can begin to add additional team members.

If you feel your team’s goals need more people, you may be aiming for results that are unattainable in the time period your company would expect them. Take some time to plan out the specific goals that you see feasible in a time period that allows you to show management the benefit of investing in this project. From there, you can look to expand on a company-specific basis based on project adaptability.

4. You’re trying to move too fast

By setting realistic results with a small team, you should inform executives when you’ll likely start to see results by. Many big data projects equate a large team with fast results and often end up disappointed and a part of the 85 percent failure statistic. Big data obviously has many benefits to a company and, when used correctly, can help in all areas from financial to customer satisfaction. However, many projects aren’t getting to experience this due to the false perception that these results happen quickly.

As TechRepublic states in their coverage of big data failure, “in general, however much vendors may want their customers to go big with big data, the last few years of rampant big data failure suggest that a far better way is to start small, and build slowly. Let [developers] experiment and grow projects organically. Given the current 15% success rate of big data projects, it’s time to try something different.”

5. Your view of data is hurting your efforts

Companies tend to see data as something they get from running their business, a byproduct of their main efforts. However, executives and employees alike should be valuing it “as a strategic asset to the company.” With this mindset, it makes using data to aid business practice a necessity, instead of a simple side project that one hopes to see results from.

Once this view is established, it’s going to allow the project to flow into your workplace environment at a faster and more efficient pace. This is because, like any project that a company deems salient to success, you will be given the time and resources to map out “the strategy and priorities regarding skills are defined.” This will set your team up for future success, as “a critical success factor for its implementation is the ability of the organization to build, grow and sustain a multidisciplinary team to address the identified business problems.” However, a company needs to view and value the work of the big data in this way in order for their efforts to grow within the company.

Final Thoughts

These are exciting times for big data, but that excitement can encourage people to jump too quickly into ambitious projects. You can determine how to succeed with a big data project, but it’s all about proper planning. Take these lessons to heart and get ready to power up your project. Here’s to your future big data success.

Patricia Bajis bio: Patricia works for Benzinga, a Detroit-based media outlet, where she creates educational content surrounding investing, insurance, and banking. She recently earned a B.A. in English Language and Literature from the University of Michigan.