Dear Executive, Without Advanced Analytical Skills, You're Not Employable

In today's connected economy, can HR effectively recruit the very best talent if they're not social?
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In an effort to better understand the role of big data and analytics in business, Michael Krigsman and I connected with two brilliant industry veterans -- icon and leading human resources technology management expert Naomi Bloom, and business analytics executive veteran Nenshad Bardoliwalla.

We started our conversation with a historical perspective on the importance of data and analytics in business and the fundamental importance of data in today's connected economy. We agreed that CIOs and CMOs must have analytical skills, and solid understanding of business processes, to make informed decisions based on the best use of data.

All the data we have is about the past, so how do we use theories about the future to make smart decisions? "We are very short on the human capability, by company, to figure out what would be the right analytics. Who needs this information? How to we get this information to them so they understand? Delivering the right data, to the right person at the right time is human resource management challenge and the HR community needs to get in front of this," said Naomi Bloom.

We also talked about the use of predictive analytics in business. "The reality is that the real skills problem we have is the skill of the average business people is to understand the output of analytical systems. To think analytically." said Bardoliwalla. Most CMOs are not well versed in data analytics. CMOs must have statistical and analytical skill sets. We have a massive retooling and skills training need or people will be left behind.

We talked about data scientist shortage of 190,000 by 2018 and yet PhD engineering hires are less employable -- 60 percent employed after 1st year of graduation in 2002 versus less than 40 percent in 2012. As we discussed we do not have a solid business process understanding in business. We also talked about immigration problems that constrain us from keeping talented new graduates in the U.S. The last challenge is startups recruiting highly skilled data experts based on higher salaries.

We also discussed how enterprise software is difficult to use. We need to move from structuring systems from machine processing to human processing. We have access to more computational power -- technique in visualization and text mining is enabling better usability and performance success, said Bardoliwalla.

We discussed improving business agility by bolstering our Human Resource Management capabilities -- we need to deliver better decision making at the right time with the right context to improve the quality of decision making -- example is compensation and succession planning. It's not just mining the data and presenting in expressible ways, its providing at the point of sale, said Bloom.

We also talked about gamification in the enterprise and use of big data. A key point was correlating decisions to better outcomes are key to improve greater adoption of analytics in business. We need systems that learn the impact of decisions and correlate desired behaviors and the role of incentives. We referenced health care benefits and role of HR and big data to encourage the right behavior and rewards.

In today's connected economy, can HR effectively recruit the very best talent if they're not social? "No, the function needs to be social and people need to be social. The best people will not work for companies that are not social. Not just the HR department but the whole process of recruiting must be social," said Bloom. I also shared our social recruiting process of hiring a six-figure salary marketer using Twitter only and not accepting resumes. Ms. Bloom noted that using social networking can help us find global talent, while significantly reducing recruitment costs.

Is it fair to expect CIOs and CMOs to be analytical and data driven? Perhaps a more viable answer is to appoint a chief data scientist or a chief data officer? "All executives must develop analytical competencies or in 18 months they are going to be doing something else," said Bardoliwalla. It doesn't matter if it is fair to expect executives to become data scientist and analytical, but it is a must. Titles don't matter -- there is a body of work to be done, we must distribute the work to the people who have the right skills to get the job done, said Bloom. "It is a wise individual who elongates their career by continuing to move with the needed skills." Bloom.

I really enjoyed my conversation with two brilliant data and technology industry experts, Naomi Bloom and Nenshad Bardoliwalla. All business executives can greatly benefit from this 50-minute video of our conversation. In summary, the path of success for executives is: big data -> big insight -> big actions -> big value to customers and employees. To successfully complete the path, business executives must place a stronger emphasis on developing their own analytical skills and also ensure their employees, management, and overall business is well trained and equipped to use data as competitive differentiation.

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