Transforming the Data-Driven Culture starts from the Top: How to get your CTO to embrace Data-Driven Strategy


In a previous post I discussed why companies need a Data Strategy and not just more Data People, in this post I want to breakdown, the number one reason, why most companies who want to become Data-Driven struggle at it and how to overcome it.

As I described in my previous post, “Become Data-Driven or Perish”, there are four steps any organization needs to go through, before the implementation of your strategy can be initiated. Namely;

  • — First, Make someone responsible for data,
  • — Second, align the organization’s key aspirations with the Data Value Chain,
  • — Third, develop a strategy in line with those aspirations, and
  • — Fourth, attract the talent needed to fulfill the strategy.

Technology-driven or Data-driven

Whenever I discuss why someone needs to be responsible for Data with companies, I often notice that the Chief Technology Officer or the Head of Development are the ones that are the most critical about why this is necessary. The reason for their criticism doesn’t come from a mistrust in data, but more from the notion that most CTO’s are unable to see the ROI of becoming data-driven, let alone introducing a new executive member who is fully responsible for data.

Most CTO’s see it as their responsibility to examine the short and long term technical needs of an organization, and utilize capital to make investments designed to help the organization reach its objectives, but until now most companies have yet to make the case for the capital investment in Analytics, Data Science, Big Data, Machine Learning and AI, to convince most CTO’s to make this decision.

So when discussing data as a driver, the first reaction of a CTO is often that Technology should not be decided by the Data Strategy, but that the technology needed to develop a solution, should be the basis on which others can derive data and use the results for their decision making.

To illustrate, if you are building a tech company and the founders are in the early-stage of development, the CEO will lay out the case for the need of a customer, he or she might act as the Product Owner (in absence of a CPO) and lay out what needs to be build to solve a customers problem. It is then up to the CTO to decide and create the infrastructure necessary to build it.

Most CTO’s will build the product based on their previous experience, using the stack they are most comfortable with, often not worrying about the future needs. The Minimum Viable Product they are building needs to solve the initial problem and as the company will grow the job of the CTO will change in finding new ways to scale the infrastructure and capabilities of the platform.

So when you introduce a Chief Data Officer, Head of Data or anyone else who is responsible for Data, that brings with it a different way of looking at the infrastructure and what has been build, which leads to most CTO’s knee jerking reaction.

For example, a company who is building an application (imagine the next Uber, Tinder or WhatsApp) can decide to use Apache Tomcat as the app server, a JAVA application to write the code and PostgreSQL for the database, all this running on top of a Linux server. Which sounds like a great way to start, but as succes and growth enters the picture, introducing a Data-Driven way of working and scalability, would need significant changes to the core of the platform, to allow the Analytics and Data Science capabilities that are required to become truly data driven.

How to deal with a resistant CTO?

It wasn’t so long ago that the CTO role was introduced. During the end of the 1990’s, and the beginning of 2000’s, the CIO (Chief Information Officer) oversaw IT, but with the escalating complexity of information technology many companies allocated some of the responsibilities from the CIO to the CTO.

Nowadays most new companies are Technology-driven, so the role of CIO has been fully replaced by the CTO. The CTO in mostly dot-com or other technology-oriented companies where information technology is key, is responsible for determining how technology can be used to implement the business strategy, but then subsequently, the CTO is responsible for actually integrating and running the technology, i.e. the role of the ‘operations manager’.

As Big Data, Machine Learning and Artificial Intelligence, give companies the opportunity to become truly Data-Driven, CTO’s need to be informed that the role of a CDO or Head of Data is not to replace or threaten the CTO, but to become a partner in implementing new data-driven technologies into the technology stack.

Provide examples of Data-Driven companies that have incorporated new technologies with the existing Stack
By truly understanding the current infrastructure of the company, the underlying technologies and researching which products align with what has been build, CDO’s/Head of Data’s can turn CTO’s into advocates rather than antagonist. By showing how the core infrastructure can remain the same, but that Data is the layer that can sit on top of the Technology infrastructure, CTO’s can be shown that the investment even a very small one can already impact the technology for the better.

Start with a MVP and let the results speak for them self
Luckily devices have become significantly stronger in processing power over the last two decades, so much so that a Data Analyst/Data Scientist, can use an application like RStudio or Python to create an Minimal Viable Product. If the database can be accessed through the Command Line, there are easy ways to pull the data directly into RStudio or Python. Using different packages, a Data Analyst can create dashboards to show how Analytics can provide the business with insights into the data stored in databases.

Data Scientist can go a step further and show how cleaning, massaging and organizing (Big) Data, can lead to new products or services or enhance existing ones. Showing this locally, can open the door for a production version, that can be integrated with the existing technology.

Create a non-technical use-case to make your point
With the shift of business from non-digital to digital, we have the ability to access data that is generated outside of the company. Everything from Marketing, Sales to Human Resources, generates data that provides opportunities to improve and build a use-case to show the potential of becoming data-driven.

The website implemented with Google Analytics, gives companies the ability to improve the website performance, increase leads or sell more products. E-mail marketing through Mailchimp, Customer Relationship Management through HubSpot or Human Resources through ADP, all provide massive amounts of data that can be used to improve conversion, lead-times or reveal insights into employee behavior. By using non-core data to improve the business, board members can be shown the benefit of becoming data-driven and build the case for the CTO to get on-board.

Don’t force it

In the end it all comes down to changing the culture of an organization, not by pushing or top-down enforcement, but by building a case for why Data should have an executive’s full attention. Just like two decades ago, when companies started hiring CTO’s, because of the Technology-driven approach that created some of the biggest companies in the world. The latest phase of the Information Age, gives companies who truly embrace the Data-Driven way of working, the ability to differentiate themselves and grab market share and profits, that companies who are unwilling to adapt are leaving on the table.

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