May 15 2014

Print this Post

Making Sense of Enterprise Manufacturing Intelligence

manufacturing_intelligence_visibilityManufacturing is a complex industry, so any technology that promises to provide transparency into operations, or clarity around buyer and supplier trends, is certainly a welcome addition to a company’s software stable. The problem is that often the technology used to gain visibility into enterprise operations can be just as complicated as the business problem manufacturers were trying to solve in the first place. Clearly, this is not a viable solution strategy!

There are a myriad of choices in extracting greater knowledge and intelligence about your operations: Do you need business intelligence (BI), business analytics, predictive analytics, or big data in the enterprise? The lines blur further when it comes to the factory floor. Is BI for manufacturing the right fit, or is Enterprise Manufacturing Intelligence (EMI) the better choice? Or, perhaps it’s all of the above?

First of all, what works for the enterprise might not work well on the plant floor — these environments use completely different metrics and processes. So, the rule of thumb #1 is: don’t expect a business intelligence system — even with a manufacturing component — to be able to effectively measure the variables on the plant floor. This BI vs. MI debate has been explored in greater depth in this earlier post.

Second, figure out what it is you want to measure to know what variation of intelligence and analytics you need.  BI will measure front office issues, like sales, revenue, and expenses, but the solution itself is really just a reporting mechanism that is dependent upon pre-calculated key performance indicators (KPIs).  Business analytics allow more on-the-fly analysis using data mining to find new patterns and relationships. Predictive analytics takes it a step further, including mathematical and statistical algorithms to forecast future events. But the volume of data is getting so big — as in “big data” — that the analytical tools must evolve to handle large sets of structured and unstructured data sets.

All of these capabilities can be integrated together as part of a larger enterprise system. But, in order to extract information from the production floor, you really need a completely different type of approach. This type of software solution is most commonly called an Enterprise Manufacturing Intelligence (EMI), or for more of a plant-based system, simply a Manufacturing Intelligence application. Each of these IT systems has a set of functions for measuring equipment activity, production, and employee performance.

Because MI is built specifically for plant floor conditions, many systems will include pre-configured data-mapping to make it easy to access real-time operational performance. But, to get the most out of your system, make sure the MI system integrates with the manufacturing execution system (MES), and, just as importantly, includes quality measurements as well as Business Process Management (BPM) for contextualization and propagation of the information to the right person at the right time.

Ultimately, it is the people in the organization who need to have access to and benefit from BI and MI. So, the last point — delivering the right information to the right person at the right time — is the biggest piece of the puzzle. That’s a whole other issue (for another post), as it requires industry-specific customization, mobility, and the latest trend of implementing self-service options that empower the people. More on that later …

Permanent link to this article: http://www.apriso.com/blog/2014/05/making-sense-of-enterprise-manufacturing-intelligence/


  1. electronic cigarettes legal

    Hi there, its good article about media print, we all understand media is a great source
    of facts.

  2. Tadeusz Dyduch

    Interesting post. The only point I would add is that EMI must also handle complex data integration with multiple shop floor systems spread across physical locations.
    This is not trivial if we consider distributed master data management, different time zones, languages and most importantly different source systems that have their own life cycles.
    Many BI platforms provide some level of interface monitoring but ETL configuration and deployment is often poorly supported in that context.
    EMI tightly coupled with shop floor system (particularly those in level 3 of ISA95) has a chance to mitigate many of the issues.

  3. learn to play piano keyboard

    Hello colleagues, good paragraph and pleasant urging commented
    at this place, I am actually enjoying by these.

Leave a Reply

Your email address will not be published. Required fields are marked *

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>

Time limit is exhausted. Please reload CAPTCHA.