“The greatest enemy of business progress is not ignorance, it is the illusion of knowledge.”
Tomasz Tunguz, partner at Redpoint Ventures, together with Frank Bien, CEO of Looker, dive into organizational challenges and opportunities managing the deluge of big data in their book Winning with Data. Many of the recently disruptive companies are leveraging data as an operational asset and outmaneuvering the competition by removing the bottleneck of access and use of synthesized data. Four core problems discussed include breadlines (aka demand), obscurity, fragmentation, and brawls (aka miscommunication).
The authors provide a high-level discussion of how most teams and organizations can transform into a data driven culture, evolving how people make decisions, collaborate and operate.
In working with data and intelligent systems for a better part of my career, it’s been an interesting journey engaging with how various companies in different industries can be led astray by this ‘ignorance’ which Stephen Hawking refers to in the above quote. While there’s a bit of self-promotion, the book delivers on a number of obvious and newly discoverable case examples where operationalizing data has made a positive impact on visibility and efficiency. In the progression steps outlined, the most common threads revolve around simplifying access and improving data literacy.
"When we say data-driven, we're talking about companies that operationalize data….We were talking about workers who wake up every morning and use data to tune their actions throughout the day."
The internet has enabled so many more people to share, collaborate and innovate. Data democratization, a common theme throughout the book, realizes the same broad opportunities for insights, decision making and innovation.
Data democratization means breaking down various silos and having access to data when and where it is needed at any given moment by anyone. Security, a valid concern in data access, does require someone dedicated to execute proper governance without stifling potential insights. The authors describe this as an operational necessity to invest in building an asset for any organization. Empowering more people increases the chance for more revenue opportunities.
Recruit and Shape Your People
"We learn only when we have both the curiosity to ask a question and the tools to answer it. To change our cultures, we should celebrate and reward curiosity."
Curiosity is a trait found in everyone within a data-driven organization. These are the people who are willing to experiment and investigate. Enabling these people with tools and encouragement for their curiosity increases the overall learning of a team. Coupled with that curious nature, having people who are open to asking the right questions improves an organization’s learning about itself and the possibilities for growth.
These attributes remove the common business fallacy stemming from a ‘HiPPO’ (high paid person’s opinion) where decisions are dictated by seniority without evidence or consideration of facts. As the authors bring to light, data not only serves to provide better decision making for anyone at any level, but making the data work for you can enhance a company’s ability to adapt and thrive.
One of the most interesting concepts discussed in the book is the use of ‘gemba’, Japanese for ‘the real place.’ In the business context, gemba refers to observing and executing on continuous improvement practices where ‘value is created.’ For manufacturing, it is the factory floor. Gemba is one of the core concepts that elevated Toyota to becoming a leader in manufacturing. For SaaS based technology organizations, value is created within the data. The concept drives consistency, reliability and accuracy across teams in an organization. Support teams structured under gemba can now effectively deliver data education and training for groups as well as aggregate the needs of the entire organization.
Understand and Manage Data Bias
"...Illusion of validity fools us into believing that gathering more data will help us predict the future better."
It’s in our nature to have data biases. Gaining awareness training is imperative combat them. The book outlines some of the most common in data literacy:
- Survivorship – Survivorship bias materializes when we omit certain data from our analysis. The remaining data, containing the survivors, leads us to draw a faulty conclusion.
- Correlation vs. Causation – While data may move in tandem (correlation), both data sets may not truly explain the effect of one another.
- Anchoring – Anchoring bias occurs when you are asked to consider a value before estimating.
- Availability – If an event can be more memorable, we believe it to be more probable.
- Illusion of Validity – The belief that gathering more data will help us predict the future better.
Hiring the right people who ask questions, and encouraging data-driven discussions can improve better decision making skills.
While a high-level read, Winning with Data does provide a great blueprint for how to tackle the data revolution within your organization. The book could be better organized, but consider the topical categories of tools, training, data, and people as you read or take notes. Also, I would like to see more resources available of examples of companies transforming data cultures for greater benefits. If you do follow much of the startup ecosystem either for wisdom or inspiration, I highly recommend following Tomasz Tunguz either on social media or via his personal blog.
Tunguz and Bien, while sharing the infrastructure and tools to support a data-driven organization, emphasize that the real secret sauce still comes down to the people first.
Who in your organization loves data enough to lead your data-driven culture change?