An Era of Change is Upon Us

Most people have heard the saying “the only constant in life is change.” Change comes at us from all directions, and it is relentlessly driven by the many events and factors that swirl around and impact us every day. 

The communications profession certainly is not immune to the forces of change.

In fact, because of the coronavirus pandemic, many organizations are seeing unprecedented levels of change to their business models. Every department is being asked to adjust and innovate to weather the next 12-24 months until the world (we hope) passes through the pandemic. As a communicator, if you already have not been asked, it is likely you soon will be challenged to find a way to do business smarter, faster, and more efficiently. Unfortunately, efficiency is often sought out by trying to do the same work with fewer people who end up working longer hours. 

But such a challenge also creates the perfect opportunity and motivation to rethink what you do and how you do it. 

Times of transition are strenuous, but I love them. They are an opportunity to purge, rethink priorities, and be intentional about new habits. We can make our new normal any way we want. 

– Kristin Armstrong, Three-Time Olympic Gold Medalist

Taking what some call a “zero-base approach” to your work can be a lifesaver. Zero-base planning means rethinking from scratch how you do your job, where you invest your resources, and how you make your team more focused and effective together. And frequently zero-base changes deliver a cathartic moment that pays huge dividends.

Fortunately, in the past few years things have changed in the world of media monitoring and analytics that make this approach to planning particularly effective right now.

Things Have Changed

In recent years, many of the world’s most sophisticated brands and their communications teams have chosen to embrace a new approach to communications analytics. Instead of relying on the approach from the early 2000’s – throwing technology blindly at the problem – they have moved forward to a new, proven method that utilizes the best that technology has to offer while respecting the unique abilities that humans have to interpret complex human communications. 

Companies like Merck, Berkshire Hathaway, Exelon Energy, and many others – all with reputations for using the world’s best talent and technologies – have embraced this new approach. They have found through robust testing that it consistently generates more reliable analytics and much richer insights that make them smarter, more effective, and more efficient.

In short, people paired with technology delivered the exact improvements they were seeking.

The Evolution

So how did we get here? The evolution of media monitoring and analytics has moved through three distinct phases over the past decades:

Phase 1: Big Books (1950-2000)

The world moved slower in these times, and so did communications. Monitoring was done manually, usually with thick clip books filled with physical copies of media coverage. It was not uncommon to wait weeks or months for metrics, and communications impact often was measured simply as the thickness of the clip book. 

Often communications teams claimed success simply by talking about the stories that were written about the company and its executives. While that approach created great presentation theatrics, it rarely reflected the overall success of the communications effort accurately.

Some organizations also relied on (the now-discredited) Ad Value Equivalent, or AVE, a misguided attempt to equate news coverage with the value of ads that ran on those same pages or in the same broadcast segment.

But technology marched on, and scissors and tape no longer did the job.

Phase 2: Technology Cure-All (2000-2018)

This is the era that gave us the exponential growth of digital communications; during these years, email, text, and social media all came of age. Communications teams gained access to digital streams of any news content they desired, all delivered in an instant via the Internet. 

Communicators jumped on the idea of instant analytics, and metrics became (sometimes obsessively) focused on counting mentions and impressions, regardless of the quality, context, or sentiment. Often with this model a headline story in the Wall Street Journal was counted the same as an irrelevant mention by a hobby blogger with 30 followers, and a keyword mention was considered equivalent to a complex message pickup by an influential writer. 

On top of that, the endless pursuit of increasing impressions created a “hamster wheel” environment in communications teams, where the obsession to generate clips of any kind dominated what should have been a focus on strategic messaging and guiding public opinion. Compensation plans sometimes included counts of mentions as a key component for bonuses, leading communicators to push for stories of any kind regardless of messaging strategy and business impact.

Another approach favored by this automated model is so-called Attribution analytics. The problems with this automated attribution approach have been well-documented. In a nutshell, these attribution models use technology to connect dots in ways that do not hold up to the scrutiny of even a high school statistics class.

Over time there became an increasing awareness and acknowledgement of the severe limits of this all-tech approach. Technology was not delivering on its promise to reliably understand complex concepts and sentiment – both of which were (and are) absolutely critical to the communications function. Irrelevant articles were picked up, sentiment was frequently wrong, and complex concepts (like Innovation and Trust) were often completely missed, so the resultant data was bad.

“I don’t know what circle of hell bad data may be, perhaps it’s the third or fourth, but no matter what, who wants to live like that? No one.”

Steve Molis, Renowned Development Guru, Salesforce.com

In fact, multiple disciplines came to the same conclusion at the same time as corporate communicators, including software companies, self-driving trucks, delivery robots, medical diagnostics, and investment services. The conclusion was simple yet powerful: augmenting great technology with talented human resources was a killer application that consistently delivered the best balance of fast data and valuable, reliable insights.

Phase 3: Expert-Guided Tech (2018-    )

We are now in the third generation of media monitoring and analytics – one that has moved to recognize the limitations of technology and that has embraced the value of human-technology collaboration. Industry after industry has embraced the marriage of fast technology paired with the unique creative, analytical, and introspective nature of human experts.

With this hybrid approach and the resultant quality data and deep insights, these professionals are able to make much better decisions, focus their resources, and achieve consistently better results. With this now proven superior capability and insight, Expert-Guided Tech has become the fastest-growing segment in the media monitoring and analytics sector.

As an aside, technologists still look to software to reduce human effort and cost whenever possible. Will technology ever replace humans in these roles and understand relevance, context, sarcasm, and underlying sentiment? These challenges may well be solved someday, but despite the claims of some bold marketers, the consensus among experts is that the General Artificial Intelligence to achieve this is at best decades away.

How far are we from general A.I.? I don’t think we even know enough to estimate. We would need dozens of big breakthroughs to get there, when the field of A.I. has seen only one true breakthrough in 60 years.

Kai-Fu Lee, Former President, Google China and Author of ‘AI Superpowers’

Going Forward

So what have we learned? Fundamentally, the model of the past 15 years – fully-automated, human-free measurement – did not deliver on its promise. And like in many other industries, the approach is being tossed aside by many of the smartest minds in corporate communications. These experts have also realized that chasing mentions, keywords, and impressions is not the best use of their time and talent: every year the team was tasked to lift these (largely meaningless) counts even higher; no matter how hard they ran, they were just going nowhere fast.

Now is the time to turn over a new leaf. Things have changed, and you need to make the choice to evaluate moving to Expert-Guided Tech and seeking higher-quality data and analytics. 

Quality data is cited regularly by its proponents as being more focused, less stressful, and more efficient with limited resources. They also regularly brag about newfound strength in measuring their impact, being more competitive, and proving their worth in the organization. The approach gives Communications an equal seat at the table with more data-driven disciplines like Marketing, Sales, and Technology.

As an added bonus, this approach, when all resources are measured, is frequently less expensive than the Technology Cure-All approach. In short, reliable tech-human analytics has provided a more effective communications strategy, better measurement of impact, and a leaner, higher-performing team.

Do something today that your future self will thank you for.

Anonymous

How Does Expert-Guided Tech Change My World?

Many aspects of the communications function take on new characteristics of precision and focus when the power of technology is paired with the ability of humans to understand and interpret communications.