Decisively Digital. Alexander Loth

and looping additional people into conversations. It works great for distributed teams, across time zones and even languages. Once a conversation turns complex enough to require multiple paragraphs of text, a phone or video conversation can often be the more efficient tool — ideally scheduled in advance so participants have time to prepare or invite other subject-matter experts.

      Alexander: How about collaboration? Which approach could a distributed team use to work together on a whitepaper or a sales deck?

      Patrick: Platforms like Microsoft Office 365 or Google G Suite offer great collaboration tools for all kinds of documents and are integrated with chat solutions such as Microsoft Teams or Slack.

      Alexander: How could a company skill up their employees fast without leaving anyone behind?

      Patrick: By having access to well-crafted training through a learning management system, employees can learn at their own pace. By selecting solutions that are leading in user experience and similar to consumer services, companies can shorten the time to productivity and increase employee satisfaction.

      Alexander: What will happen to companies that do not level up in digital maturity and organizational readiness?

      Patrick: The workforce of today and tomorrow expects to be able to work from anywhere and at any time. Not offering and working with state-of-the-art technology is not only a competitive disadvantage but also a disadvantage in attracting the best talent in the labor market.

      Alexander: Do you see a chance in low-code environments for employees to design business processes without software development skills?

Patrick: By moving enterprise software from what used to be custom on-prem solutions to globally available cloud solutions, data and services have become a lot more unified and accessible. With that, marketplaces for plugins and extensions for thousands of enterprise scenarios have become available for every solution. Automations that required a team of highly specialized engineers only a few years ago can now be created in drag-and-drop interfaces in a matter of minutes.

      Alexander: Ten years from now, how do you think our workplace will look?

      Patrick: In tech, one of the key trends we have witnessed over the past 10 years is that more and more of companies' tech stacks got commoditized. Where companies had to entertain data centers and have teams of engineers available around the clock to maintain infrastructure, we now have smaller DevOps teams that can provision services with infinite scaling capabilities at the click of a button. The result is that most of the workforce are working on creating customer value, at the core of companies' DNAs. I imagine this trend will expand to other, nontech sectors of the market through more outsourcing and usage of highly reusable platform concepts.

      Alexander: Why do data visualizations have such a strong impact on our decisions?

      Patrick: The old adage “a picture is worth a thousand words” still holds true for modern-day businesses. Data visualizations can be made up from millions of individual data points but still convey an insight while just glancing at them. They can provide insights into past performance and real-time trends, are used to forecast future KPI development, and often are the language that subject matter experts use to drive conversations with higher-level executives, such as a company's leadership team.

      Alexander: Why is data storytelling the essential data science skill that everyone needs?

Patrick: A few years ago, the act of just collecting data is what put many companies ahead of the curve. Today, it is hard to imagine not having data available. It turns out that just having data, often very raw data, is only a fraction of the equation. Being able to interpret data and understand it in the very context of a business and derive insights and suggest actions based upon it are important skills that enable us to extract true value out of data.

      Alexander: How can everyone learn to communicate better with data?

      Patrick: Without data, conversations are often driven by personal experiences and expectation bias and are generally subjective. With objective data in the room, conversations become a lot less emotional and a lot more focused on the subject matter. The key to communicating with data is to have data. Whenever we introduce a new process or change an existing one, we should ask ourselves how we can measure objectively whether the change had an impact. Oftentimes, we will find ourselves in situations where we don't have the perfect tools at hand to measure what we would like to. Surveys and other techniques can help us to bridge technology gaps and at least get us to a point where we have some data.

      Alexander: Companies usually have plenty of legacy dashboards, the messages of which cannot be seen at first glance. What would a workshop to improve visual data communication look like?

      Patrick: Dashboards lose their value if people lose trust in the data that is presented on them. Having a strong data framework in place that defines key KPIs and the very measures that go into them helps deliver a consistent message. At scale, this often means that companies have to come up with their own internal data dictionaries.

      Alexander: What basic guidelines and patterns should always be considered for an expressive visual dashboard?

      Patrick: The key goal of dashboards is to deliver insights at a glance. In order for that to be true, the data on dashboards should be visible at all times — which means that they need to be responsive to or optimized for the presentation layers they are used on without requiring users to scroll or click them. To turn a data point into an insight, [a dashboard] also needs to provide guidance to its relative context. It is unclear whether 5 of something is good or bad. Five of something on a colored scale from 1 to 25 turns that data point into an insight.

Alexander: Who should you trust with helping you monitor the changes you are making and testing your dashboard prototype to see if it meets expectations?

      Patrick: Three stakeholders come to mind: the owner or creator of the data, the consumer of the data, and — depending on the sensitivity of data — a legal or data-security role that confirms that the data presented respects privacy regulations and conforms with legal requirements.

      Alexander: Why should companies set up an Analytics Center of Excellence as part of their digital strategy? What are some strategies for setting this up?

      Patrick: To do data analysis right, companies need resources that are skilled to do the job and have the priority and time on their hands to do so. Most of the time, neither of the two is true for people, and teams try to do data analysis on top of what feels like their actual job. Successfully implementing an analytics strategy requires deep understanding of the processes and metrics that drive business outcomes. A good approach to get to the scope of work for an Analytics Center of Excellence is to start with interviewing future consumers of data and business stakeholders to be able to build a data framework for the company.

      Alexander: What are your personal top three dos and don’ts for an engaging visualization?

      Patrick: Keep the visualization simple and easy to grasp, provide guidance or links to a drill-down, and provide as much context for the data as possible — such as a target KPI or a cohort comparison.

      Alexander: Thank you, Patrick. What quick-win advice would you give that is easy for many companies to apply within their digital strategies?

      Patrick: Focus on simplicity and transparency.

      Alexander: What are your favorite apps, tools, or software that you can't live without?

      Patrick: Snowflake, Tableau, DBeaver, MongoDB, Slack, Trello.

      Alexander: Do you have a smart productivity