Analytics plays a critical role in manufacturing—without modern analytical capabilities, manufacturers often find themselves in a reactive mode to changing business conditions. But how do you get started with manufacturing analytics and what are the use cases most relevant to you?

The pace of business has never been faster—customer needs and expectations have never been higher. Whether you’re a B2B or B2C manufacturer, the ability to deliver the right product on time and in full to your customer is key to meeting and exceeding customer satisfaction. Order fulfillment is now considered a critical aspect of the customer experience. Getting it right helps your sales team, and ultimately your business. If you’re not highly responsive to your strategic customers and reliable to all, you’re leaving the door open to your competition.

In this blog, we will discuss what manufacturing analytics is, the business case for analytics in the manufacturing industry, the benefits of implementing manufacturing analytics in your organization, the different uses cases for manufacturing analytics, and how to get started.

What Is Manufacturing Analytics?

Analytics is the discovery, interpretation, and communication of meaningful patterns in data for the purpose of decision making. Analytics plays an important role in manufacturing—whether it is to improve overall efficiency across the supply chain, increase productivity and profitability, or to better understand and meet customer demands. Manufacturing analytics help to control costs while improving speed and quality across the board.

What Is the Business Case for Analytics in the Manufacturing Industry?

The world is less predictable than it once was. Manufacturers must be responsive to changing customer needs, demand for reduced cycle times and product innovation, competitive pressures, and global disruptions, while doing more with less to drive increased profitability and revenue growth. The new normal requires that manufacturers have greater visibility into demand and their own performance to take advantage of opportunities and minimize losses.

Without modern manufacturing analytics capabilities, manufacturers often find themselves on their heels in a reactive mode to changing business conditions (shifts in demand, supply constraints, etc.). The information tends to arrive too late for decision makers to act while there is still time to adjust course. Modern analytics enables increased visibility that allows manufacturers to minimize costly firefighting and rework and be more responsive to customers and their changing demands.

What Are the Potential Benefits of Manufacturing Analytics for Your Organization?

Most manufacturers know that better, trusted, and timely business information should lead to better decision-making. They do have questions, however, about how to operationalize this capability to drive ROI. In some cases, they have made investments into tools but have not seen significant value creation. Often, they have lots of reports and dashboards but lack the business information they need, when they need it.

To unlock the value of analytics, manufacturers need to define the end-to-end problems they experience in day-to-day operations that have the greatest impact on business performance. Starting with a data strategy, you can identify, quantify, and prioritize the business use-cases for analytics that will drive profitable growth.

What Are Common Use Cases for Analytics in Manufacturing?

Each business is unique and the use cases that drive value creation depend on your strategic goals and the current level of analytical maturity of your organization. Modern analytical capabilities provide the means to break down informational and functional silos to remove blind spots that impact top-line growth and bottom-line efficiency. Integrating the data for cross departmental value streams, such as order-to-cash, enables decision-makers to proactively manage the performance on the key measures that drive revenue growth and margin expansion.

Here are some opportunity areas for the application of modern manufacturing analytics:

  • Organic Growth: Establishing the right set of customer KPI’s such as Customer Expansion Revenue, Customer Lifetime Value, and Cost to Serve allow manufacturers to proactively drive profitable growth. Modern manufacturing analytics enables sales and marketing teams to analyze what products at what price by region maximize sales and margin.
  • On-time and in full delivery (OTIF): Delivering the right product, in the right quantity, to the right customer, at the right time, is all part of the overall customer experience. The success of OTIF is a critical aspect of customer satisfaction. Establishing and managing the right set of KPI’s allows you to identify and resolve the root cause of issues.
  • Customer Segmentation: Manufacturers face trade-off decisions when managing demand, inventory management, profitability, and customer satisfaction. Segmenting customers by volume, profitability, and strategic value allows you to ensure you are highly responsive to your most valuable customers and reliable to all.
  • Demand Forecasting: The new normal has caused manufacturing executives to rethink their S&OP process to be more agile and responsive to a highly dynamic marketplace. Manufacturing analytics enable greater visibility and accuracy into changes in demand, needs for product innovation, and help enable leaner inventory management.
  • Inventory Management: It is critical to have visibility into all inventory everywhere, down to part number, across the company. Modern manufacturing analytics provide a complete view of what and how much you have, and where it is so that you can more accurately plan to be highly responsive to your strategic customers and reliable to all.
  • Industry 4.0/Overall Equipment Effectiveness (OEE): OEE measures how well manufacturing equipment is utilized compared to its full potential. Data from PLC’s and sensors can be leveraged to automate and optimize availability, quality, and rate to maximize capacity and reduce cost of goods sold. IoT data from shop floor can also be leveraged to predict maintenance needs and determine the root cause of unplanned downtime.

How Can I Get Started with Manufacturing Analytics?

Getting started with manufacturing analytics does not need to be difficult. Here are three key steps to take before diving into manufacturing analytics:

 

1.) Assess Your Analytical Maturity: 

Buying into analytics does not necessarily mean you have to buy into the latest, shiniest technology platform. Before you make those decisions, it is helpful to define the limitations of your current capabilities. What are the persist complaints and issues? Depending on budget availability, you can right size a solution to meet your immediate needs and develop a plan to scale as analytics start delivering a self-funding ROI model.

2.) Find Your Business Champions: 

If your organization is unsure of the potential business value of developing a modern analytics capability, determine which business leaders are interested in learning more about how data can help the organization improve performance. Work to build a committee of cross functional leaders with the charter to evaluate the potential impact that modern analytical capabilities could deliver to your organization.

3.) Identify Your Business Priorities: 

Before you decide to implement analytics software, work with the data champions of the organization to brainstorm the use cases that would move the needle on your strategic priorities. Engaging an experienced analytics partner to lead you and your team through the process can help drive alignment when prioritizing the opportunities that will best serve the enterprise goals.

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