As the collective desire to optimize big data grows, your company is probably facing many decisions, and you’re not alone. Every organization is trying to determine what kind of investment is right for them and how data can make the biggest impact on their goals. One of the most important questions to ask before moving forward is this: who should handle data at your company?
The Chief Information Officer, or CIO, has been a popular title as of late, but before taking the plunge, it’s important to examine whether or not it’s the right fit for you. What is the scope of your company’s data plan? It might require a c-suite executive for leadership and development, but chances are, you’re not there yet. Your personnel investment as it applies to data might be better structured in another way.
The data scientist is another appealing hire for the data movement, but again, its necessity depends on your company’s structure and data plans. Even then, a good one might be hard to find. Three years ago, McKinsey Global Institute reported that by 2018, the United States will suffer an alarming shortage of 140,000 to 190,000 people with the deep analytical skills needed to make data-informed business decisions. Your company might not have the scope or data access to invest in a data scientist yet, but if you do, there’s still another option to consider.
As you make progress in data optimization, you might want to think in broader terms when it comes to staffing. A diverse, multidisciplinary team with varied skill sets is often the best way to harness the complexities of data. This is especially true for large companies with the interests of multiple departments at stake. Different people bring fresh perspectives to the table as they address big data adoption and technology challenges. A team mindset is helpful in decision making, and it’s often more cost effective to provide training for existing employees who have knowledge of your company than to hire new ones and start from zero.
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