According to the Journal of Consumer Research, a high price indicates either bad value or good quality, whereas a low price indicates either good value or poor quality.

At the heart of this dichotomy is the role that quality plays in both the actual and perceived price of the product. To understand how quality plays a critical role in pricing, one must look at the stakeholders affecting the price in manufacturing.

A proper focus on pricing must take into account customers’ perceived value of the product and what they believe that value is worth, i.e., what they are willing to pay for it. Without this, engineering and marketing team members are left to develop pricing from a bottoms-up, cost-plus approach: How much are the raw materials, cost of assembly, cost of delivery, and so forth? Often, marketing simply tacks on a percentage of profit to the order to establish the price. For them the calculation is simple math that ensures they will hit margin goals. However, they are not the folks in the field convincing customers to buy. Nor is the engineering team listening to customers’ objections or value perceptions. 

As usual with Quality Digest’s diverse audience, this year’s top stories covered a wide range of topics applicable to quality professionals. From hardware to software, from standards to risk management, from China trade to FDA regulations. It’s always fun to see what readers gravitate to, and this year was no different.

Below are five articles that garnered a lot of interest from our readers. As you can see, the topics are quite diverse.

Improve Risk Management and Quality Across the Value Chain by Increasing Visibility
by Kelly Kuchinski

How will the United States’ withdrawal from the Paris Agreement affect greenhouse gas emissions? Quality Digest editor in chief Dirk Dusharme and Mike Richman, principal at Richman Business Media Consulting, point out that most manufacturers already recognize that waste, including waste of energy as represented by carbon emissions, costs the supply chain money.¹ This leads to my conclusion that withdrawal from the agreement will not have any significant effect on U.S. carbon emissions.

Involving relevant interested parties

It is a basic principle of ISO 9001:2015 that organizations must identify the needs and expectations of their relevant interested parties, but not all interested parties are relevant. The Paris Agreement offers little identifiable value to organizations, so it is not a relevant stakeholder. Neither are investment banks that had hoped to profit from cap-and-trade mandates.² The supply chain should contain nothing that does not deliver value to the other supply chain participants.

Good salespersonship is a species of street smarts. It’s about quickly sizing up your customers and pitching your wares in terms that reverberate with their unspoken needs and desires. As artificial intelligence (AI) and machine learning increasingly intersect with e-commerce, these priceless human skills are finding algorithmic analogues—not just at point of sale, but throughout the customer journey.

The results will be familiar to online shoppers everywhere. Netflix’s and Amazon’s algorithms leverage the data from each customer click to fine-tune their recommendations and drive consumption. The tech behemoths also deploy consumer activity data to sharpen their email and social media marketing. This is likely only the beginning because the technology’s predictive prowess is improving all the time.

The food industry is evolving rapidly, with consumers demanding quality, authenticity, and transparency from food manufacturers. And they’re not just demanding it; they’re “voting with their dollars,” supporting companies that align with their personal beliefs. To keep up with consumer demand—and to keep up your bottom line—it’s important to understand their needs and make changes that support them.

In doing so, you can improve your product quality, reduce waste, inspire brand loyalty, compete more effectively, and avert potential media or food-safety disasters. Let’s look at six ways to improve product quality in food manufacturing.

Manufacturers face constant challenges of rising expectations as customers and regulators demand better quality and greater traceability throughout the supply chain. Exacerbating matters are unpredictable tariffs, which necessitate faster responses to changing trade barriers and regulatory requirements. These factors must all be accomplished at lower costs while coping with already thin margins.

The solutions to these challenges already exist within current systems. Unlocking the value of data already in systems generates actionable insights from quality control and quality assurance for operations and plant-floor management.

Improving the entire manufacturing process allows manufacturers to optimally monitor costs, remaining within a range of profitability. If data (i.e., business intelligence) show information outside the acceptable range, it can be quickly adjusted.

Put in the terms of this article’s title, most of us would run a mile, whatever the proposition. But the popularity of online reviews, and the trust we place in persons unknown when making major decisions about where to stay, what to eat, and how to get the most from a trip, tells a different story.

Online communities have always been a place where people connect with peers: people like us, sharing something in common. Accessible anywhere and generally free to participate, it’s little wonder that news groups, forums, and chat rooms flourished from the beginning of the internet and prepared the ground for the late 2000’s social media explosion.

It’s hard to imagine a world without these connections. They’ve become part of the fabric of our daily lives. They’ve changed not only the way we socialize and define our friends, but also our relationship to information and how we form, and express, our opinions. They’ve also influenced the way we make our vacationing decisions; many of us now move from idea through research to booking entirely on screen.

A recent family biking vacation in the Dolomites region of Italy had my family and I all swept up in the charms of Northern Italy. Snow-capped peaks near the Austrian border, endless apple orchards, award-winning Chenin Blanc, and quaint Italian villages with healthy doses of affogato (strong espresso coffee meeting with gelato is sheer genius) made the 250 km fly by.

By the time we ended our trip in Riva del Garda, we were mentally separated from the harsh Minnesota winter and ready for the summer. We couldn’t stop talking about the outfitter (Scottsdale, Arizona-based Pure Adventures) that arranged this active vacation. However, when my wife got an email with a $500 referral incentive from them, she was reluctant to exercise it, despite many colleagues expressly asking us about the company that arranged this trip. She did not feel comfortable getting a substantial reward for something her friend or colleague did.

Therein, lies the conundrum of getting referral marketing to work. To be clear, Pure Adventures had the right idea to try to use existing, ostensibly delighted, customers to acquire new customers. The nuance lies in how to activate and even accelerate this process using financial incentives, when at its core, it is primarily an intrinsically motivated action.

Faced with a growing range of tech solutions in marketing, from AI to big data to blockchain, business-to-business (B2B) companies too often choose the status quo. Recent evidence suggests the divide between success and failure is not about how much companies spend, but how well they integrate technological solutions that create value.

In other words, a company’s digital investment does not necessarily translate into marketing return on investment (ROI). For that to happen the firm needs to build a digital marketing organization—data-driven marketing capabilities around the customer. 

A pivotal and enduring dimension of success in B2B markets lies in the relationship a company has with its clients. Thus, identifying the type of relationships that you have or would like to have with your customers is an excellent starting point to select and embed digital technology into your strategy. And this process is increasingly important for B2B companies if they are to maintain growth even as digital disruption accelerates the shift from B2BigB to B2SmallB.  

Do you know what a retailer and a tightrope walker have in common? They both have to balance. For the tightrope walker, the logic is clear. But what’s the balance that a retailer is looking for?

A typical dilemma of shortages vs. storage costs

Although the dilemma of shortages vs. storage costs is applicable to any product category, it’s much more painful with perishables. If their quantity can’t meet the demand, retailers should be ready to see a frown from an unhappy customer who didn’t find her favorite dairy, fruit, or vegetable on the shelves.

However, staying on the safe side by ordering more perishables is hardly a cost-effective solution. Perishable products require special storage conditions, and their shelf life seldom exceeds a couple of days, which means retailers must address disposal issues. So, it’s easy to understand why retailers, by all means possible, try to find the optimal balance between storing too much and too little.

A way of handling this dilemma with data science

There is a way to handle the storage/shortage dilemma efficiently: It’s via a deep neural network (a DNN), the most advanced data science approach.