Executive Briefings

Three Problems in Manufacturing That Impact Productivity and Profitability

Despite the advanced technology now available, there are still three key issues that adversely affect manufacturers of all types and sizes: data management, inventory, and gross margin.

Three Problems in Manufacturing That Impact Productivity and Profitability

Although each has its own silo, they are also interrelated. For example, consider the use of data. The way data is gathered, analyzed, and understood can have a significant impact on the decisions made, inventory strategies that are established, and ultimately a firm’s profitability.

Data Management Matters

Data management is not for the cowardly. For middle- to large-sized firms, mounds of data are typically generated, which is great for those who know how to make sense of it. Unfortunately, very few know how to process this much data. This is the point where it can become problematic. The traditional process involves bringing a company’s data into a data eco-system, and then bringing in business intelligence hardware. Management then assigns a team of analysts to assess the information, and then — voila — the numbers are expected to reveal what needs to change in daily operations. However, it never works that smoothly. Instead, many companies fall victim to what the industry calls “analysis paralysis” or ending up with so much data that it’s hard to imagine knowing what to do with it. Once a company reaches a certain volume of information, evaluating findings, making observations, or picking up on patterns simply isn’t as easily approachable. Perhaps this is why it is no secret that the ability to make sense of data diminishes the faster a company’s data ecosystem grows.

In an ideal world, data management would serve as an income generator. But, without access to someone who understands the what, why, when, and how behind the numbers, companies run a high risk of chasing misleading clues. How does a company learn to get a solid grasp of the data being generated? It begins with gaining visibility into the process — into everything occurring — in some cases down to the minute. A good starting point is to look at some of the questions associated with data management and what they represent:

-How do you visualize the information that drives your business? (year-to-date profit/loss; pending orders; order fulfillment; customer satisfaction/score cards)

-How do you make the right decisions required to grow your business? (goal creation and recognition; personnel effectiveness and performance; market awareness and trends;cohesiveness throughout the business)

-What are the current sources of data you use to measure, analyze, and sustain a true business reality? (how much or volume of data; variety and type of data; velocity of data; value of data)

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Although each has its own silo, they are also interrelated. For example, consider the use of data. The way data is gathered, analyzed, and understood can have a significant impact on the decisions made, inventory strategies that are established, and ultimately a firm’s profitability.

Data Management Matters

Data management is not for the cowardly. For middle- to large-sized firms, mounds of data are typically generated, which is great for those who know how to make sense of it. Unfortunately, very few know how to process this much data. This is the point where it can become problematic. The traditional process involves bringing a company’s data into a data eco-system, and then bringing in business intelligence hardware. Management then assigns a team of analysts to assess the information, and then — voila — the numbers are expected to reveal what needs to change in daily operations. However, it never works that smoothly. Instead, many companies fall victim to what the industry calls “analysis paralysis” or ending up with so much data that it’s hard to imagine knowing what to do with it. Once a company reaches a certain volume of information, evaluating findings, making observations, or picking up on patterns simply isn’t as easily approachable. Perhaps this is why it is no secret that the ability to make sense of data diminishes the faster a company’s data ecosystem grows.

In an ideal world, data management would serve as an income generator. But, without access to someone who understands the what, why, when, and how behind the numbers, companies run a high risk of chasing misleading clues. How does a company learn to get a solid grasp of the data being generated? It begins with gaining visibility into the process — into everything occurring — in some cases down to the minute. A good starting point is to look at some of the questions associated with data management and what they represent:

-How do you visualize the information that drives your business? (year-to-date profit/loss; pending orders; order fulfillment; customer satisfaction/score cards)

-How do you make the right decisions required to grow your business? (goal creation and recognition; personnel effectiveness and performance; market awareness and trends;cohesiveness throughout the business)

-What are the current sources of data you use to measure, analyze, and sustain a true business reality? (how much or volume of data; variety and type of data; velocity of data; value of data)

Read Full Article

Three Problems in Manufacturing That Impact Productivity and Profitability