Business Intelligence Blog from arcplan
9Mar/120

Big Data for Manufacturers: Customer Feedback Should Influence R&D

by

In 2001, The McKinsey Global Institute published a comprehensive report on big data, Big Data: The Next Frontier for Innovation, Competition, and Productivity, which explores the value that companies across various industries may yield as result of the big data explosion. So far we've explored the impact of big data on retail and healthcare companies, but today I'll explore how big data analytics impact the manufacturing industry.

The manufacturing sector stores more data than any other sector, according to the McKinsey report. Manufacturers will likely get the most benefit from big data analytics since they have so much "raw material" to work with (from machinery metrics to sales systems). Manufacturing is a relatively efficient industry, with many advances made over the last few decades to streamline processes and improve quality through management practices like lean & six sigma (and lean six sigma!). But big data can be the impetus for the next wave of improvements in manufacturing, especially in R&D.

Research and Development
Streamlining the R&D process results in greater efficiency and reduced costs for US manufacturers and is important for products to be competitive in the global economy. But in 2012 and beyond, manufacturers should be going further, leveraging big data to influence design decisions. This means incorporating customer feedback into the process, designing products and adding features that customers actually want. McKinsey calls this "design to value" or "value-driven design."

Surveys: I've taken consumer surveys that ask questions like "How much more would you be willing to pay for x feature?" and I now understand why companies are asking this. They are culling data from consumers about what features are desired and if they are included in the product/service, what is the value, i.e. how much are people willing to pay for it. Gathering concrete insights is one step toward big data analytics influencing R&D. Manufacturers should be listening to what consumers want and refining their designs accordingly. It's just smart business.

Here's a concrete example: Domino's Pizza. You might not think of Domino's as a manufacturer, but it is – the company is a serious dough manufacturer, producing and distributing dough to more than 5,000 US stores. A few years ago, the company started tracking big data amounts of customer feedback. They implemented a transactional survey on their website, which asked customers to rate the food they received, and they started tallying social media comments about the company. The feedback was mostly negative, particularly about the pizza crust and sauce. So they mined the data looking for clues as to what customers wanted, revamped their pizza recipe and launched a TV and social media campaign that resulted in a 9% rise in sales that year. With more than 1 million customers ordering Domino's food every day, their customer feedback campaign generated massive amounts of data. Big data was the impetus for the company to reinvent its recipe and re-engage lost customers and the effort paid off.

This idea can certainly be done at a smaller scale for smaller manufacturers – customer feedback in such large quantities is not a requirement for influencing R&D. I'd advocate that customer feedback in any amount can positively influence R&D. Think about instituting a customer advisory board and enlisting the help of trusted customers to generate new ideas for products or refine existing products. Just because it's not big data does not mean it won't provide valuable insight.

Social Media: Earlier this year, I saw a commercial for the new Honda CR-V which advertised a social media-type contest called the Leap List, where entrants can make a list of things they would like to do before taking their next leap in life (it's like a less morbid version of a bucket list). Not surprisingly, guidelines for the contest suggested that the list include something you would do with your CR-V. With this information, which is likely huge in volume and timeliness, data analysts at Honda are going to learn more about customers, get a better idea of their ambitions, personalities and preferences, and will be more in tune with what they may need out of a vehicle. We'd probably be surprised at how much a contest can influence product design (and product marketing as well).

The Barriers: Okay, getting these big data insights seems great, but in reality, it's hard work. Large manufacturers are going to have to engage with marketing, advertising, and focus group firms to develop the surveys, contests, and social media engagement necessary to get customer feedback. That can be costly and time-intensive, but as seen with the Domino's Pizza example, can pay huge dividends.

Another barrier is the issue of disparate data sources. Your sales data is probably stored somewhere separately from your product lifecycle management (PLM) data, which is separate from your customer feedback. We see this issue all the time at arcplan. Every manufacturer wants and needs better reporting that draws from multiple source systems. This is a strength of ours, since arcplan has more than 20 native data connectors, including big data sources like SAP HANA & Teradata, and allows business users to access and analyze this information in real-time. So it's a problem that's easily solved by the right software.

But then you have the issue of information sharing; manufacturers require insights not only from their side, but also from distributors and retailers who may be unwilling to share data they consider a competitive asset.

The fact is that if manufacturers can convince their network to share data, the results can be huge – the McKinsey report cited one telecom company who used customer feedback to increase gross margins by 30% in just 24 months. They simply used the feedback to identify unnecessary features and include highly desired features that could command a higher price tag.

Mining customer feedback – big data or not – is a great way for manufacturers to develop new products and revamp existing ones. Have you undertaken a customer feedback initiative at your company? Any success stories to share with readers?


More about arcplan + big data: arcplan is not limited to small data volumes. In addition to our more than 20 data connectors, arcplan Enterprise supports analytical solutions on top of SAP HANA and Teradata. arcplan has a native connection to SAP HANA and connects directly to Teradata's OLAP Connector. Our unified platform includes arcplan Enterprise for reporting and dashboards and arcplan Edge for budgeting, planning and forecasting. E-mail us for more information.

arcplan

About arcplan

Follow @arcplan on Twitter for the latest news about our solutions and events!
Comments (0) Trackbacks (0)

No comments yet.


Leave a comment


No trackbacks yet.