Business Strategist / Operational Strategist / Automation / Smart Systems / Industrial Networks / Efficiency

"Intelligizing" your manufacturing business

It is critical to take stock of the data you do have and the data you don’t.

By Bob Bedard, president and CEO of deFacto Global

The industrial and digital revolutions created an upheaval and urgency prompting manufacturers to continually transform their businesses or risk losing ground to competitors. Organizations gain or lose advantages depending on their ability to optimize their business processes using automation and digital technology and now a new wave—let's call it Intelligizingis emerging that promises to have at least as powerful an affect on businesses as previous waves.

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deFacto Global's Bob Bedard

 

Intelligizing a manufacturing enterprise includes harnessing the power of data and intelligent applications to transform running the business. Cross-enterprise, intelligent applications including business planning, business intelligence and artificial intelligence are core building blocks of an intelligent analytics strategy. The latest versions of these products are making the best use of large volumes of data that are now available.

The path to Intelligizing requires a strong foundation. The three basic building blocks to Intelligizing are:

1)     A business-intelligence solution

2)     An intelligent corporate-planning solution

3)     AI capabilities integrated with a manufacturer’s information infrastructure—corporate planning, ERP, MRP and other systems—including machine learning (predictive models, recommendation engines, forecasting), chatbots, neural networks, audio/visual processing, etc. 

Business intelligence sets the stage

There is a strong correlation between business outcomes and data. We all know this.  Establishing business intelligence (BI) tools throughout the organization enables visualizing data to make better decisions. We know this, too. 

The first step is to recognize how data affects business decisions, a critical step that includes taking stock of the data you do have and the data you don’t, then correlating that to key business decisions. This step usually involves the use of a BI tool that can dramatically help visualize data and envision how that data informs various decisions.

Corporate-planning systems act like the brain

But BI tools are somewhat tactical in that they are good for visualizing data but not for structuring data (especially financial data) across the organization. And they don’t have the robust planning and analysis capabilities found in corporate-planning systems. 

In fact, in an intelligent company, corporate-planning systems should be able to act as the “brains” of the information infrastructure. They aggregate key data from around the organization (ERP, MRP, CRM, HR, etc.), structure it and add the necessary business intelligence to model individual parts or the entire business.

AI makes that “brain” smarter and faster

Once a company understands how data affects business decisions and has their data in a form that can be easily analyzed and accessed, then more advanced analytics can be applied in a purposeful and meaningful way. Examples include machine learning for predictive forecasting/recommendation engines and AI applied to business processes. Or consider a chatbot used to generate very specific data that an organization needs. In evaluating this data, you can identify any missing information needed for personalization, product planning, customer service, etc.

The next step is to apply AI to that data to enable smart higher-level decisions.

Manufacturers are becoming more adept with analytics (or at least more analytics aware). But many are struggling with a clear understanding of what AI and advanced analytics really are and how they can solve mission-critical problems.

Sound familiar?

Obtaining a demystifying, working knowledge of these technologies, a clear understanding of problems to be addressed (many of which are common across manufacturing businesses), and a practical pathway to approach the problem is very much within the reach of every manufacturer.   

Want more AI? Find our library of resources here.

 

 

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