Capturing voice of social network and using it

Brian X. Chen reports in the January 2 2013 Bits section of the New York Times, "The iPhone Goofs Up on Telling Time, Again," that the new Do Not Disturb (DND) function on iOS6 iPhone failed to turn off for many users on New Years Day.

This is a new feature that allows iPhone users to set a quiet time (like when you sleep) to block incoming calls and alerts. It is suppose to turn itself off at a pre-determined time so that calls, alerts, and alarms can be heard.This bug is even more noteworthy because it is featured in a new television commercial airing this week. NYT readers first blasted Apple for the bug, and then turned on themselves for whining about such a small inconvenience.

This brings to mind two QFD concepts. The first is the famous "Sales Point" column in the quality planning table room on the right side of the House of Quality matrix (or done independently in Blitz QFD^®) where a selling point is given extra weight which eventually strengthens the improvement calculation for related technical requirements. Below is one example of a HOQ with Sales Points weights (the yellow highlighted column).

The purpose of the "sales points" column has been frequently challenged as it seems to do the same job as the relative importance and the level-up columns, and is thus redundant. Dr. Akao's purpose, however, was to add a sales point value when the associated customer need is going to be promoted, as in the case of this Apple commercial. The added weight would direct engineers and software developers to  pay more attention to its auto on/off functionality.

The second point, I commented myself back to the New York Times:

"I see the DND issue as one of software quality. Developers often have incomplete or inaccurate use cases around which they design their features and code. They do not fully understand how the feature gets used in real life, and so sometimes get it wrong. Like the proverbial mushroom, they are kept in the dark and fed s**t!

It is comments from users like you who post here that can provide the necessary insight to do the job right the first time. There are methods for analyzing the voice of the customer, like QFD, that actually build on your feedback and help marketeers and engineers do their jobs better. So keep on blogging and contributing your experiences - we will all benefit."

My second point is that every opportunity to get customer feedback should be welcomed by a company. Many companies do monitor social media as part of their customer relationships management (CRM) programs, but not all companies forward the information to new product development departments.

The customer voice table is the QFD tool for analyzing these comments. In order to give engineers direction for improvements and next generation products, negatives and complaints should be reversed into positive statements, and technical solutions should be translated into product independent customer needs.

Related Reading...

• QFD for Software and IT Projects

• QFD for Predicting Future Technology Risks

• Trusting Front Line Employees To Be Customer Advocates

• Learn Blitz QFD^® tools ... QFD Green Belt^® Certificate Course

Social Media for VOC

In a recent New York Times article "Facebook, Twitter and Foursquare as Corporate Focus Groups" on July 30 2012, it was noted that producers of hit food and other retail fads are using social media to extract new ideas from consumers, as well as to select which ideas to commercialize.

Younger consumers who are more adept at online communications and can be attracted in larger numbers and more quickly than traditional focus groups. Further, their online profiles are self-populated and can provide much more demographic and attitudinal details than otherwise obtained. Sorting responses by these criteria can yield valuable insight according to age, income, location, and other characteristics important to target marketing.

In recent years, several QFD practitioners have been using social media to acquire Voice of Customer (VOC) data during new product development. QFD, of course, would usually begin well before focus groups were employed to evaluate solution options, in order to acquire VOC to define customer needs and product requirements. In these cases, users are asked to send in videos and photos of their activities and frustrations, usually around a product theme. Other uses are to search personal social media postings for issues related to the new product project.

In my experience, this has proven to be a rich source of candid VOC where the user is directing the script. A kind of virtual "gemba." In one case, we uncovered that one company's product was being abused by young teens, allowing the maker to change the product and make it less prone to tampering.

Of course, like any customer gemba data, these are only inputs to a deeper QFD analysis that includes translating VOC into prioritized customer needs, product requirements, and features. These features can be tested again using social media as described in the above captioned article.