{"id":6821,"date":"2012-03-31T07:24:00","date_gmt":"2012-03-31T07:24:00","guid":{"rendered":"http:\/\/www.smartdatacollective.com\/index.php\/post\/big-data-moneyball-your-company\/"},"modified":"2012-03-31T07:24:00","modified_gmt":"2012-03-31T07:24:00","slug":"big-data-moneyball-your-company","status":"publish","type":"post","link":"https:\/\/www.smartdatacollective.com\/big-data-moneyball-your-company\/","title":{"rendered":"Big Data = Moneyball for Your Company"},"content":{"rendered":"

In every business, people have to analyze information<\/a> in real time to arrive at the right decisions.<\/p>\n

<\/p>\n

In every business, people have to analyze information<\/a> in real time to arrive at the right decisions.<\/p>\n

The problem is that very few people can correctly solve important business problems in real time. In fact, most people can\u2019t even solve these problems if they have unlimited time to do so, according to<\/a> John Lucker (@johnlucker<\/a>), a principal at Deloitte Consulting and James Guszcza, senior manager at the firm.<\/p>\n

\"Money<\/a><\/p>\n

So to avoid becoming overwhelmed, decision makers rely on their gut feelings when weighing various factors, the authors say.<\/p>\n

But people are pretty biased about the ways they make decisions \u2013 biases that can sabotage efforts to unlock the value in all the data their businesses collect. That\u2019s because the human mind just hasn\u2019t evolved enough to allow us to make the kinds of business decisions we have to make every day, according to Lucker and Guszcza.<\/p>\n

\u201cThe human brain is very bad at juggling decisions,\u201d Lucker told an audience<\/a> at GigaOM\u2019s recent Structure:Data conference.<\/p>\n

And it\u2019s not easy for businesses to overcome some of those biases, according to the author of the GigaOm article. For Lucker, however, companies have to overcome the \u201chuman factor\u201d if they want to successfully drive organizational change. The way to do that is by using statistical analytics and predictive models, he says.<\/p>\n

Take for example, \u201cMoneyball<\/a>,\u201d the story of how Billy Beane of the Oakland A\u2019s used analytics to identify undervalued baseball players \u2013 a story that has far-reaching implications for many industries. The premise behind \u201cMoneyball\u201d is that the team could do a better job acquiring new players by using a computer-generated analysis of the pertinent data than the scouts could do using their gut-feelings.<\/p>\n

\u201cMoneyball\u201d is a early example of \u201cworkforce intelligence,\u201d according to Lucker and Guszcza. And analytics can bridge the gap that often exists between workforce-related data sources and the business issues to which they should be applied. For example, they say predictive models are being built so HR managers can make better hiring decisions.<\/p>\n

However, it\u2019s just not enough for Billy Beane to have the data to back up his decisions, he also has to win over the Oakland A\u2019s execs to change the way they run the team, according to Lucker. Similarly, Lucker says while you have to have the data, you also have to establish a clear link between your corporate strategy and what you\u2019re doing with big data and analytics. If not, the new processes just won\u2019t work.<\/p>\n

Next Step<\/strong><\/p>\n

Download this complimentary \u201c5-Minute Guide to HR Analytics<\/a>,\u201d and learn the three critical capabilities a modern analytics environment must provide to your HR staff so they can adequately support the enterprise.<\/p>\n

Linda Rosencrance
Spotfire Blogging Team<\/p>\n

\"\"<\/p>\n","protected":false},"excerpt":{"rendered":"

In every business, people have to analyze information in real time to arrive at the right decisions.<\/p>\n","protected":false},"author":33,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_seopress_robots_primary_cat":"","_seopress_titles_title":"","_seopress_titles_desc":"","_seopress_robots_index":"","footnotes":""},"categories":[15,17],"tags":[994],"class_list":{"0":"post-6821","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-analytics","7":"category-decision-management","8":"tag-moneyball"},"amp_enabled":true,"_links":{"self":[{"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/posts\/6821"}],"collection":[{"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/users\/33"}],"replies":[{"embeddable":true,"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/comments?post=6821"}],"version-history":[{"count":0,"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/posts\/6821\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/media?parent=6821"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/categories?post=6821"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/tags?post=6821"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}