Analytics: Which Ones Are Right For Your Manufacturing Business?

Posted in Reporting, Analytics and Business Intelligence on November 29, 2012

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Big data, cloud, ERP, analytics — such technology buzzwords are dominating the industry. But what exactly is analytics?

With the explosion of data from social media, companies want to know what insights they can mine, according to a post on the SmartData Collective website. What exactly are these analytics insights? Well, consider the analytics in a car’s GPS system as an example. Data collection includes updated information about traffic, accidents and weather. Analytics can predict future outcomes, but also best- and worst-case scenarios.

Analytics are not industry specific. The retail sector is using analytics to maximize marketing dollars, transportation and logistics companies leverage analytics to find the best delivery routes, and healthcare service providers use key performance indicators to decide the number of hospital beds they should have.

There are several levels of key performance indicators, which increase in maturity and complexity: descriptive, predictive and, the newest, prescriptive. It’s helpful to know the difference because, like the cloud, analytics has become somewhat of a catch-all phrase.

Here are the three types of analytics as outlined in the SmartData Collective article.

  1. Descriptive: This involves collecting data, which a company may or may not know how to organize or read. Descriptive analytics asks: What happened? Through KPIs and dashboards, descriptive analytics can tell you the meat-and-potatoes of your data, like the amount of customers and revenue points.Today, Netflix uses descriptive analytics to recommend movies subscribers should watch based on their past choices.
  2. Predictive: Analytics takes place at this level when companies have built-up data sets for more than two quarters in subsequent years. Predictive analytics asks: What will happen next? This is the most common key performance indicators process discussed. Statistical methods will outline various relationships and predict outcome. This is where data mining, forecasting and predictive modeling come into play.For example, an ING marketing plan predicted who will respond to personalized campaigns, reducing direct marketing costs.
  3. Prescriptive: This reaches beyond the predictive level. Prescriptive analytics asks: What is the best course of action for certain situations? Advanced statistical optimization and simulation techniques are used, including inputs and constraints to recommend how your company should react. These kind of key performance indicators considers seasonal impacts on the company.

Amazon.com uses prescriptive analytics for price optimization based on demand.

Here lies the question: What do you think predictive analytics can offer businesses? How much farther beyond predictive analytics do key performance indicators exist? What will it take for manufacturers to embrace predictive analytics? Feel free to discuss in the comments below.

Source: SmartData Collective, September 2012

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