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Why Company Culture Matters

A recent conversation with a CEO of a start-up inspired me to do some self-reflection as well as a head-first dive into research on team culture and empathy driven development.

The team culture of a company became not just the majority of how I made my decision on whether I wanted to work with them… but that a company culture that nurtures and fosters innovative thinking turned out to be 80% of my decision; the remaining 20% made up of financial reward and the actual work and delivery. Is that unreasonable to demand that any start-up team – that has to pitch and deliver a viable product and is already under a tremendous amount of pressure – now has to have certain values and behaviors?

Not at all. Any company looking to hire “innovative” talent will quickly realize that they need to demonstrate how their culture rewards creativity, embraces change and improves as a team. While these are not competency-based skills that we typically rate our employees on at our yearly checkpoints, these are true skills… skills of charisma and diligence and contribution that ultimately form the foundation of your company’s culture.

WHAT the team delivers is different from HOW the team delivers. For example, a team can deliver a product with all of their boxes checked – hire top talent, decent business model, customers willing to pay – and they deliver despite its team culture. What might be missing from this picture-perfect view is how this team behaved in a manner that promoted compassion, trust, and understanding that created value. If we step away from our obsession to check all the pedigree-rich boxes and focus on how we can build teams that focus on delivering value, I would dare to argue that these team would be more cohesive, engage in more open communications, and deliver products that are more likely to delight the customer.

From the book Tribe by Sebastian Junger, “It’s clear that we can no longer regard success as a zero-sum game: one group rising only at the expense of another. In this new century people worldwide will rise or fall together. Our mission must be to create a global community of shared responsibilities, shared benefits, shared values. This new focus will require all of us to think about the how, and to find new ways to take action to solve the global issues that none of us can tackle alone.”

Yes- in fact, the teams that do not believe that they have the same level of impact to the company or accountability to the customer will not be nearly as effective. The QA tester or Office Manager has as much of a role in the company’s success as the Lead Developer or Sales Manager even though they impact the company in very different ways and how these individuals view each other is in part shaped by the culture and the company promotes. Their respective roles will dictate how they interact whether hierarchical or by skill set or respect for what each individual brings to the table.

What if we could take a page out of a “tribe” from back in the day where people lived in villages and shared responsibilities to ensure each others’ survival? How would we behave differently? In many ways, working at a company is like surviving together in a village. The same individuals that travel out to fight in the battlefield return to the village to hunt for meat. There is a transition that is seamless and a community that embraces what each person’s capabilities are, regardless of title or role in a particular situation. What they can all agree on is that they need each other to survive.

The most important skill for a product team is empathy. Empathy is the capacity to recognize and understand the emotions being expressed by others, and is core to a product manager’s job of representing the customer within the company. Succeeding as a product manager requires mastery of a diverse skills set, encompassing data analysis, communication, psychology, research, prioritization, UX, marketing, and software development. Their greatest contribution to the company is a deep understanding of the customer  which s/he must use to guide a development team. These days, the idea of who creates software is slowly being replaced from that guy in the basement working alone into a diverse group of people, working together as a team, that puts the needs of the people who will be using their software at the center of their development process.

We are all familiar with how not to develop products or why teams slow down. Just because you’ve managed to dodge these land mines doesn’t mean you’re in the clear. Development used to be all about silos – give requirements to the builders and they’ll come back with a finished product. Nowadays, development teams are made up of a team of individuals whose skills meld seamlessly into the others’. For example, the front-end developer understands how distributed networking concepts can deliver better website performance. Alternatively, the UX designer works closely with the database architect to surface the most insightful metrics for the customer. This kind of team culture often promotes mutual respect and, perhaps more importantly, enables the team to grow in knowledge and easily accelerate their output with higher quality. If you’ve seen these teams in action, you’ll see just how special they are because they act different. They are dynamically unified. They are fanatically competitive. They are subject matter experts and chameleons at the same time. And perhaps most important of all, they are empathetic.


Other related articles:
[HBR] The Company Cultures That Help (or Hinder) Digital Transformation
[HBR] How Starbucks’s Culture Brings Its Strategy to Life
[MITSloan] Aligning the Organization for its Digital Future
[strategy&] Building a digital culture. How to meet the challenge of multichannel digitization
In Digital Transformation, Culture Change Goes Hand in Hand with Tech Change



Adapting Data into Digital Media

“Adaptation… means watching for the next wave that is coming, figuring out what shape it will take, and positioning the company to take advantage of it. Adaptation is what drives increasing-returns businesses, not optimization.” by W. Brian Arthur, Increasing Returns and the Two Worlds of Business

In essence, this is what we have had to do as an industry as we have grown leaps and bounds in volume, saturation, profitability and capability. Our access and ability to process data has transformed the way that we conduct business, particularly in digital as our media buying has gone online, systems are automated, transactions are algorithmically driven. Data has become part of our every day language and a tool for people to make better, more informed decisions.

In the 1990s, online banner ads were introduced to be bought and sold based on a CPM, the same cost structure that is used in TV advertising. The difference is that we can track whether someone actually saw it and if they clicked on it. This introduced additional metrics — CPC and CPA — that now still exist in other forms of digital media. Fast forward 20 years, other metrics commonly include: attribution, click path, engagement/loyalty, rank, popularity, device type, shareability, value, etc. These metrics have evolved and become more complex over the years as our ability to generate, collect, process and navigate data has advanced. And the people who generate, collect, process and navigate the data have also evolved in the industry as they are multi-lingual, left and right brain, sales and technology savvy, data-lovers and most of all… storytellers.

The demand for data has never been as great and wide-spread as it is vast, across devices, platforms, media plans, content, geographies.

Until recently, data was not expected to be real-time and dynamic; it never needed to be presentable in raw form for general consumption. The handling of large data sets has traditionally been the responsibility of specialists trained in math-related disciplines (applied mathematics, statistics, engineering, and economics) with very minimal exposure, if any, to marketing functions. These specialists were typically on risk management, business intelligence, strategic planning, DBA, or CIO teams where the data was consumed primarily by a few highly trained individuals. Seldom were these individuals successful in translating the data into something actionable on the business side as they weren’t necessarily armed with the business knowledge or context and vision. This translation layer is precisely what is currently in motion, from the technical teams to client-facing roles.

Here are some recent titles that have emerged as a result of this shift:

  • Data Scientists
  • Business Insights
  • Marketing Analytics
  • Data Strategist

Companies want best of breed for both parts of the brain – this is unrealistic and rare to find unless you are Google, Facebook or Apple and can throw silly amounts of money and have a variety of interesting, large-scale projects at individuals to keep them happy get them to stick around.

In the last several years, marketing and other business teams have drastically increased the demand for data in order to make better business decisions, drive business strategy to improve profitability, optimize campaigns, analyze ROI and customer behavior, audience targeting, to create profiles and more relevant experiences to increase loyalty.

The organizational structure of most organizations are still divided into business/sales teams on one side and technology/data on the other. The data strategists and current-day storytellers will often contain elements of both sides — the analytical brain that understands how to sell solutions and ideas, the creative mind that strives towards operational excellence, the client advocate that can identify best practices.

Business teams are not ideally situated to swim through the data even if they are creating much of the demand. Some common challenges that business teams face:

  • there is a talent gap; a sales/marketing team is not likely a top pick for high quality data talent
  • sales/marketing professionals don’t have the time to sift through the data even if they have the skill set
  • the data is usually gated; deeper and broader access to data is reserved for specialized teams
  • the data is usually not architected for sales/marketing consumption
  • requirements for data use evolve as frequently as sales/marketing campaigns; this is also typically what causes friction between data/tech and sales/marketing teams
  • data scientists hired into a business team are often not properly managed, given the wrong incentives and difficult to retain

Technology teams have been completely overwhelmed and stretched