Why managers need to learn Data Analytics

Famed American academic Thomas Davenport brought data analytics to the forefront with his acclaimed article Competing on Analytics (Harvard Business Review, 2006).  Davenport spoke of how companies like Marriott, Capital One, Amazon and more had gained huge advantages over their competition by deploying data analytics.

Data Analytics makes you more valuable to your company.  You can compete on a level that many competitors are just ignoring or not adapting fast enough to.  Business has seen waves of change over the years, everything from industrialization to most recently social networking.  The key leverage businesses can gain today is in data analytics.

Word to the wise, you need to start learning Data Analytics now.  The winning manager of this era will need to rely on Big Data as much as instinct.  It can take years to gather a sufficient amount of usable data internally.  Some data will be external to the organization and can be purchased and incorporated into analysis.  The real value however, is in understanding your internal data, your resources, your processes, your trends.  Many companies are gathering data, but is it the right data?  If not, you may need to think about what type of data you need, and start gathering it.  Once data is gathered, you may need several years before you have enough of it to do meaningful analysis.  Once you finally are able to analyze the data,  you will draw conclusions, possibly via regression or statistics.  Acting on those conclusions may be premature however and lead to wrong outcomes.  So typically you would make some analysis, draw conclusions, and then after more time (perhaps a few more years), see if your conclusions were proved correct.  If so, then you know you have some data you can put to work.  All of this culminates in the ability of an organization to make predictions and forecast accurately.  Modeling and backtesting can be used against historical data and trends to understand how changes to processes, resources, supply chains, etc. will effect outcomes.

If this sounds like a lot of time, it is.  The reality is it can take as long as 5 years or more to get data analytics working in a company that has not been collecting the right kind of data.  Even if you have the right data, it can still take a while to get the data analytics practice in place.  A company has to decide to hire data analysts or train internally.  Ideally it may be a combination of both.  You then have to wrap your arms around all of your data.  Figure out what data is important, what tools will be used to analyze it, visualize it, warehouse it.  The data warehouse is important.  One thing you don’t want to end up with is a bunch of people, all with different spreadsheets of data that don’t agree with each other.  In a data warehouse you can hold all of your raw data.  The data can have a high degree of data quality.  Ideally as many people as possible would have access to the data.  People should be able to socialize around the data, make comments on the data, talk about the data, share in the data.  The company benefits, employees feel more engaged.

This is truly the era of Information.  Today companies can get easy access to the storage, compute, collaboration tools, analysis tools and most importantly the Information itself, in a timely manner, and put it to work for them.  Tools exist today such as EMC Greenplum, QlikView, Talbeau…..one can even get started with as little as Microsoft Excel.  Those who enjoy programming and having a very extensible environment may choose to deploy R, Processing and many other tools.  There is definitely value in looking into the more prominent tools.  The difference between using something like Microsoft Excel vs. Tableau is like a Ford Mustang vs. a Ferrari.

Some of the areas Big Data can be put to use in a business to gain a competitive advantage:

  • HR can use data analytics to discover what leadership and management styles are most effective in the organization based on performance.  They can then target these attributes in candidates.  This is happening today.  Many HR departments are looking at Meyers-Briggs or similar data within the existing organization, finding trends in their top performers and finally recruiting based on this data.
  • Data Analytics can be used to find out where to price your product within the marketplace, capturing as much revenue as possible without overpricing yourself.
  • Customer data can be analyzed to understand the Customer Lifetime Value.  This allows the organization to make sure they are focusing on it’s most important customers and making sure they build relationships and strategy to retain these customers.
  • Supply chain management is an important part of a company that can be optimized with data analytics.  Understanding how much inventory to keep, what the consequences will be of shortfalls in the supply chain, which parts of the supply chain are impairing a faster time to market, etc.
  • Marketing can use data analytics to understand how well a campaign is performing, which communication routes customers are using to reach out to the business or even understand how product placement within a store is influencing sales.

Even without prediction and forecasting, just having employees know the data makes them more in touch with what the business is doing.  This viral knowledge of business data increases chances of innovation within the business.  Businesses will need to adapt to Big Data by deploying the tools and infrastructure and  most importantly gathering analytics talent to make the most use of it.

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