In his new book, âFail Fast, Learn Faster,â Randy Bean uses extensive anecdotal evidence to demonstrate that businesses need to become data-driven or risk losing relevance.
Bean, who is the founder of data-driven consulting firm NewVantage Partners, has been evangelizing this message for years as a regular contributor to major trade publications and in an annual survey that documents the progress big companies are making in founding. of a data-centric culture. .
He recently sat down with SiliconANGLE to talk about how data-driven culture change is finally sweeping big companies.
Your most recent survey found that 92% of executives said the biggest challenges to becoming data-driven are people and culture rather than technology. Why do these factors continue to be such significant barriers?
It is not easy for people to change their behavior, especially in organizations that have been around for generations. There must be incentives for collaboration and cooperation. Many are lip-smacking about these things, but when it comes to individual behavior, the situation is different.
Do you see many companies effectively tackling these limitations?
We are seeing some companies investing in data literacy, but less than half of organizations say they compete on data and analytics today and less than a quarter say they are entirely data-driven. data. These numbers have even declined in recent years. But I don’t think that’s necessarily a bad thing. On the contrary, organizations are becoming more mature and realistic about their data literacy.
Are there any organizations that stand out as being particularly effective in using data?
Two are Amazon in retail and Capital One in financial services. The most successful companies are always looking to improve. When I hear someone say they have data under control, this is where I start to worry.
The rise of big data has spawned concepts such as âsilver liningâ and the use of data for disinformation. Do you believe these trends will continue?
The data has become politicized, and I guess this is representative of some of the challenges we face on a larger set of issues. History teaches us, however, that things happen in cycles. While the trend towards hard data will likely continue for a while, eventually people burn themselves out and move on.
Does mastery of data make organizations more innovative?
There is a strong correlation between the ability to use data and the ability to disrupt businesses and industries. But return on investment can be difficult to measure, and results spread over years, which is why many organizations abandon data initiatives.
There must be a balance between data and intuition; if not, we might as well abandon the world to algorithms. Emotions, intuition and reading the situation are things that algorithms do not always have the nuance to appreciate. And data can have inherent biases, as Cathy O’Neil pointed out in her book âWeapons of Math Destructionâ. Unconscious biases can enter algorithms and data can reflect these biases.
How quickly do you think a consensus is emerging around the role of the data manager?
It has been mediocre to date; only a third of organizations say the role is well established. Some banks are in the fifth or sixth iteration of the CDO. But I think the role of CDO is now established. Over the years, our survey asked what people envision for the future of the CDO role. Until recently, only a quarter of respondents said it was only a temporary role, but it’s a very small number now.
The role is accepted but organizations are still struggling to define it. Half of the organizations in our survey say there is not a single person responsible for data across the organization. It’s more decentralized in many cases.
You also write a lot about AI. What do you think makes an app smart?
Throughout my career, AI has existed, but there was not enough data to do meaningful analysis. The work was done with samples. Now, the computing power makes it possible to examine every transaction you and others have made. That, along with the ability to capture online transactions, has increased the amount of data that AI has to work with.
Some people have great fears about unleashing AI, but AI has also failed to do some of the things it was supposed to do. It’s a mixed bag and there will be roles for machines and people for a long time to come.