Begin with discovering what customers have proven they are willing to pay for. Most companies analyze sales data to determine a pattern that can be used to improve either the products themselves or their marketing. Some businesses employ surveys, market studies, and other research to try to get a clearer picture. However, these methods tend to look at what customers did, so projections based on these data predict only what is likely to happen if nothing changes.
Of course, the chances of nothing changing are pretty low. The current marketplace is characterized by volatile demand, short product cycles, and global competition. It is far more likely that demand will change than stay the same. It’s a key reason why forecasting is such a difficult task to perform with any accuracy.
APICS educational offerings and methodologies such as quality function deployment emphasize the voice of the customer (VOC)—actual expressed desire for product functions and features—as an essential tool for understanding what the customer wants. VOC implies a direct dialogue between supplier and customer to get information on needs, wants, and intentions.
Social media challenges
Meanwhile, more companies are becoming aware of the possibilities and risks of social media and other new data sources that might provide a look into customer thoughts. Facebook, Twitter, and hundreds of other sites are attracting an overwhelming array of comments, recommendations, criticisms, rants, opinions, and complaints. Much of this is noise and of little use to a product developer or supplier; however, there are valuable bits of information out there. The challenge is finding those gems and adopting them into your design and marketing, where they can help tailor products and programs to deliver that all-important customer value.
Social media data, website clicks, user group discussions, and the like are all part of the big data phenomenon you are hearing so much about these days. Companies desperately want the information buried in big data, but they are challenged by its volume, variety, and velocity—characteristics that make traditional data tools unable to process big data—as well as the difficulty of identifying the useful information and integrating it into existing systems.
Software companies are busy striving to address these challenges. In the near future, it’s likely you will see your enterprise resources planning and customer relationship management systems connecting to big data. It will be one more way to provide insight into your customer’s perception of value.
Reprinted from APICS Magazine: Enterprise Insights. May/June 2013