Is Big Data The Key To Redesign-To-Cost Implementation?

Big data could be an important foundation to redesign-to-cost implementation. Here are the reasons behind this and why it's so vital.

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December 10, 2018
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PTC published a fascinating study on the impact of big data on product design. Their white paper illustrated a number of ways that big data can play a valuable role in the evolution of new product design and implementation.

“Big data is going to impact many industries, and product design is no exception. That’s in part because engineers will increasingly design sensors and communication technology into their products—like the Google car. In fact, some expect 50 billion devices to be attached to the internet by 2020! There are a number of ways design engineering might change as a result of IoT and the big data it enables.”

However, the post focused mostly on traditional manufacturing and product design applications of big data. In actuality, big data can be more valuable for new manufacturing solutions, including re-design to cost.

How is Big Data Playing a Role in Re-design to Cost Strategies?

Re-design to cost applies to an existing solution (product or service) that is already on the market. The objective of this approach is to develop the most optimal solution possible in terms of costs and perceived value. To do this, a whole process is organized around the entire cost of the solution, while maintaining or even improving the perceived value and reducing unnecessary costs. This would be very difficult to deploy without a good data strategy in place. Big data enables brands to better assess and control costs. They can use predictive analytics to understand the cost of materials used in their projects, as well as the evolving logistics of marketing and other functions. The vast majority of a product’s costs, between 80% and 90%, are determined during the product design phase. According to James McCannon, a data logistics expert for a leading manufacturer that we spoke with, big data helps by providing a clearer picture of the variables that come into play, such as:

  • Delays,
  • Major changes in the design of a sub-assembly,
  • Changes in specifications during the project,
  • Marketing choices at the end of the project,

Companies collect data sets around all of these functions. This makes it easy for them to develop effective controls and implement the best systems to control and automate the design and manufacturing process.

What Are the Other Roles of Big Data in the Process?

Sagepub has written several pieces on the relevance of big data in the product design process. Conggang Yu and Lusha Zhu’s piece “Product design pattern based on big data-driven scenario” was one of the most compelling. However, these papers tend to focus too heavily on a single aspect of the process. There are other implementations that are even more important.

  • Functional analysis:

This analysis is used to define the functions required to meet actual customer needs and their relative importance and valuation, in other words the cost associated with each of these functions.

  • Value analysis:

The value analysis allows an objective cost breakdown of the product/service through the definition of the target costs of the components, while respecting the functional specifications. These two analyses require an overview of the product and use different levers to reduce, change or delete a function with the same or higher performance level. These levers are based on the entire product value chain, which must be considered as a whole, and include in particular:

  • A redesign work as such of the product/service. This can involve questions that are sometimes basic, but not part of the teams’ practices, or an analysis of the competition that can lead to some good practices.
  • Ensure the efficiency and optimization of the production chain, particularly with regard to the quantities produced, but also possible synergies with other products in the range or standardization of components.
  • Review the purchasing strategy and choice of suppliers based on objective cost design in order to identify possible higher margins on certain components.
  • Redefining marketing specifications may be necessary to validate the right need of customers.
  • Supply chain optimization can also be a major cost reduction lever, sometimes within a few millimeters of a package in a different position.

Overlooking only one level of the value chain can lead to large unnecessary and, moreover, easily reducible costs if considered in the project as a whole. The redesign to cost work therefore requires the collaboration of the various entities of the company among themselves but also with their suppliers. Although historically applied to products, redesign to cost can also be applied to services or processes.

In Sum, Big Data is an Essential Component to Re-design to Cost Implementation

Numerous studies have emphasized the importance of big data for design, manufacturing and logistics management. However, most of the topics have focused on traditional design applications of big data. There are other ways to utilize big data, such as with improving re-design to cost management and other ways to streamline design and manufacturing for lower costs.