We are currently living in the digital age and are drowning in an ocean of data. Organizations have a large number of data entities and data elements, and a large volume of data corresponding to the same, and they continue to amass more and more data with each passing day. With the large amount of data coming in, it’s important to know what is “quality” data, and what isn’t.

Data entities, elements, dimensions... oh my!

Before we continue, let me explain a little data terminology as it pertains to databases, or data storage. “Data entities” are the real-world objects, concepts, events, and phenomena about which we collect data. “Data elements” are the different attributes that describe the data entity. Thus, a data entity serves as the container that comprises all the data elements that describe it.

Consider a machine shop that has many types of machines: CNCs, lathes, presses, and the like. A “machine” would be the data entity representing a physical object sitting on the shop floor, and the data elements might be machine type (e.g., CNC), machine ID, machine name, machine make, machine location, machine uptime, and so forth, which store attribute values for the different machines.

‘It’s the shoes!” Spike Lee yelled into the camera on the Air Jordan ads.

But it was never the shoes. Michael, Magic, and LeBron would have outplayed their leagues in golf cleats.

It was never the shoes.

But it was us, the salespeople. In our case, the intelligencia that “trains” people to be lean, agile, or whatever.

In companies all over the world, we are convincing people that success lies in the shoes. In huddles or iterations or A3s or DMAIC or story points. All these tools are not even hard tools, like hammers; they are conceptual tools, like voting. We don’t seem to get this.

When someone who has experience looks at these tools, we don’t see the tools; we see the results we’ve enjoyed in the past. We are strangely blind to the failures of deploying them or the near misses (which our brains will inevitably turn into wins). So, when we describe these tools in classes, we describe them with a high degree of certainty that whoever touches them will be successful.

Our classes are so convincing that we, strangely, even convince ourselves.

Even though we always struggle with clients to get them to “just do it.”

You would expect a building where vinegar is made to have a sour smell, highly pungent, perhaps with a whiff of apple. World Technology Ingredients (WTI) smells nothing like this. Their manufacturing facility, off a county two-lane in Jefferson, Georgia, has a vaguely mineral aroma. More dry than dank, and not altogether unpleasant.

Maybe that’s because the vinegar made here isn’t destined for grocery store shelves, but for food preservation. It’s called buffered vinegar, an all-natural additive that protects meats and other products from microbes. WTI makes a lot of this vinegar, more than it used to, in fact, and that’s partly because of Damon Nix.

On this Friday afternoon, Nix is taking a visitor through WTI’s plant, pointing out its sectors and stations. Here’s the wet vinegar, seven titanic tanks and even more smaller ones, emitting a hiss-and-motor chorus of mechanized blending. Over here’s the powdered version, mixed in towering contraptions on chalky floors (that will later be cleaned), then heated, blended, and bagged.

Have you heard of a media company called T-Series? Chances are, you probably haven’t. Gulshan Kumar, whose résumé up to 1983 read, “Fruit juice seller, streets of New Delhi,” founded it that year. Since its inception, T-Series has become an unlikely media powerhouse—its YouTube channel has 119 million subscribers. To put that in perspective, The New York Times, which was founded in 1851, has a total subscription base of 4.7 million across print and digital. The T-Series channel also has 90 billion views. That’s the equivalent of every human on the planet, including babies and people with no access to the internet, having watched 13 videos each on this channel.

According to the Nov. 14, 2019, issue of The Economist, media giants in the past five years have been battling for viewers’ attention and have spent $650 billion for acquisitions and content. As The Economist puts it, with wry understatement, “There will be blood.” In this shifting media landscape, how are brands going to win at getting their customers’ attention and emotional engagement? In this opinion piece, we will explore five modern principles for winning brands.

Legislative support is growing for the reimbursement of care delivery via telemedicine. The Centers for Medicare and Medicaid Services (CMS) and the Office of Inspector General have recently made final and proposed rule changes to stimulate greater use and access for telemedicine delivery. These changes mean that for healthcare providers all around the United States, telemedicine will become a greater strategic focus.

Three major areas of telemedicine affected are remote patient monitoring (RPM) services, chronic care management (CCM), and opioid use disorder (OUD) treatment. Here we highlight the most significant changes that will impact providers in 2020 and beyond.

Remote patient monitoring (RPM)

Until recently, this contributing technology for telemedicine has been hampered by murky details within existing law. It is now, however, the area of the industry experiencing the most significant changes in recent rulemaking.

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.