Business Analytics Seminar with Gary Cokins

Highlights of Gary Cokins Business Analytics seminar

Business Analytics

         Last month I attened Business Analytics seminar by “an internationally recognized expert, speaker, and author in performance improvement systems and cost management” : Gary Cokins.

         My slideshare presentation in the bottom of this post summarizes Gary’s informative and thought-provoiking presentation. In fact, some statements in this post were provoked by this seminar. Gary started by quoting Jeanne X. Harris :“40% of important decisions are not based on facts but rather on intuition, experience, and anecdotal evidence.” Arguably, we could improve the world by basing our decisions on facts, and making better decisions in the process. In addition, better decisions result in better actions, saving us time, effort, money, and other resources. The “actions” part is really important in terms of differentiating Business Analytics from Business Intelligence.

         We are all caught in the media hype of dealing with Business Analytics, and Business Intelligence. Most of us even use these terms interchangeably. However, Business Intelligence is limited to answering existing questions, and churning standard, canned reports. It is reactive in its nature: think observing historical stock performance of your favorite company without having any view on its future closing price. Business Analytics, takes the next step: it helps us gain insight, make better decisions, take action, and ultimately solve problems. It answers the questions we didn’t know we had. It adds dimensions to our questions, and helps us answer the most complex of them. There are numerous domains that touch us in our daily professional and personal lives, all influenced by Business Analytics:

     Retail: Does anyone take part in the Black Friday craze?
     Marketing: How do we track customer satisfaction with our business?
     Financial Services: Why do you think your auto insurance premium went up after your last claim?
     Text: Sentiment analytics is a relatively new field gaining traction, thanks to Social Media – are you sad with the results of Facebook’s mood study?
     Human Resources: How many seasonal workers will New York’s Department of Transportation employ during this Winter season?
     Police: Time will tell if LA becomes a safer city due to their efforts in preventing crimes through analytics.

         Business Analytics requires use of statistics to answer questions and predict future results. However, any knowledgeable analyst should distinguish between correlation and causation in their data observations. Inferential or Predictive Analytics takes a proactive approach, using statistical analysis to forecast future performance, mitigate risks, and optimize your company’s strategy. In addition, such analysis will reduce uncertainty. Forecasts can help us place procure for our raw materials being delivered at the right time, while predictive modeling will help us most efficiently distribute our final goods.

         The concept of Customer Lifetime Value is crucial for your business. While you might have some profitable customers in the short-term, you might want to focus on lower-margin customers having longer lifetime value, since they are your customers for a long run. Business Analytics can help us evaluate customer value, not just profitability. In addition, it can help us devise a more successful customer acquisition strategy: do we want to acquire customers for the sake of acquiring customers; or should we focus on attracting our ideal customers only? Finally, incentivizing your customer base might seem like a no-brainer, however, a great analyst should be able to prevent us from over-spending on customers, who would have shopped us anyways; and under-spending on marginally-loyal customers. Finding the equilibrium in this equation will yield the highest financial returns..

         As we could see, Business Analytics offers too many viable benefits to be overlooked. We need to try to overcome any existing barriers (technical, perception, organization) and implement an analytics framework in our decision-making process.

   SlideShare version of this post.

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