Even within the last year, the role of the CIO has seen rapid changes. Foundry’s latest State of the CIO research highlighted a clear shift toward operational priorities, as the CIO role expands strategically in the business. 77% of surveyed heads of IT said the CIO role was elevated due to the current state of the economy, and they anticipated this new visibility would continue for some time.
IT has always been about tradeoffs between present ROI and future innovation. But lately, the tradeoffs have become even more dramatic. CIOs are in a uniquely tricky spot right now, with requests to lower budgets coinciding with the push from leadership to incorporate generative AI across the business.
A job that used to be about managing infrastructure has morphed into a strategic business role that is all about equipping users with the technology they need to deliver business outcomes. Or, as Alteryx CIO Trevor Schulze said on a recent episode of the CIO Exchange podcast,
“The Modern CIO has to be both a technologist and a business person. And they’re building a bridge between the two.”
“It’s an amazing and crazy time to be a CIO. We’re really witnessing a once-in-a-generation inflection point.”
So, what’s the playbook for a once-in-a-generation inflection point? There is none. Every CIO is dealing with unique tradeoffs, depending on business needs. Which is why it can be helpful to identify which archetype most closely fits your CIO or other technology leaders. It’s a great way to clarify opportunities for your organization and consider how to lean into your strengths.
Identifying Your CIO Archetype
What goes into determining a particular CIO archetype? It is undoubtedly about the type of person – and leader – you are. But your business needs also shape your archetype as well as the culture you seek to build, and the legacy you want to leave.
Which one of these fits you the best?
- The Facilitator: You enable your teams and your business through technology. You are focused on providing team members with the right tools and resources and facilitating their upskilling through technology.
- The Guardian: You are a security-focused leader prioritizing data protection and compliance. (One often finds this type in heavily regulated industries or particularly vulnerable companies.)
- The Innovator: You embrace new technologies to stay ahead in a competitive market. You like to allow the business to experiment and try new things to seek a more positive impact. (One often finds this type in fast-moving, fiercely competitive industries in which having best-of-breed technology can make a huge difference.)
- The Transformer: You are a makeover specialist. A big part of why you were hired was to update legacy systems to modern infrastructure. (One often finds this type in large legacy enterprises managing a combination of on-prem and cloud technologies.)
Do any of those sound familiar? Are you a combination of multiple archetypes? Read on to see how your archetpye informs what you do next!
How the Data Stack Looks for Each Archetype
Now that we’ve identified our four archetypes, let’s go one step further and determine what each CIO’s data stack might look like. Remember, these are leaders under very different pressures in companies with diverse needs – and at different stages of their respective digital transformations. So they’re balancing different tradeoffs.
The Facilitator knows that the best business decisions come from business-driven data insights. As a result, the Facilitator’s data stack needs to be available to all, truly self-service from start to finish. A data mesh culture may be a good fit here, which prioritizes domain-driven ownership of the data pipeline. The technologies you choose should prioritize business users who may not have the technical skills to work with modern data tools, such as a SQL-based warehouse. The Facilitator also understands that to enable self-service, you need good governance, ensuring the right people have access at the right time.
- Start by choosing a data warehouse/data lake that gets this balance right (e.g., Snowflake, Redshift, or BigQuery) to build a foundation for self-service data access.
- Then, choose intuitive, accessible analytics tools that are easy to learn and don’t require code, all while leveraging that data warehouse. That last part is important; it’s how you get more value from your technology investments, while making the analytics process seamless from end to end.
- Invest in upskilling and data literacy programs that enable employees to seek and question through data, ultimately changing how they operate and make decisions.
The Guardian must build a data stack that prioritizes security and governance standards. They need technology that meets regulatory requirements, high security thresholds for use, evident data governance, and access policies. They’ll prioritize secure data storage solutions and robust access controls. Here are a few critical questions for them to ask and answer:
- Do we need a data catalog (e.g., Databricks Unity Catalog support) to enforce data governance policies and establish data quality standards?
- Do our analytics tools respect role-based access controls for the different data sources we need to access?
- Are your data workflows well-documented and auditable? Do you have end-to-end traceability, with records of where, why, how, who is using data and running workflows?
The Guardian will evaluate and choose only data management tools that meet their robust requirements. They will have at least some of their data in private storage and private processing to meet regulatory needs. And when they design a data architecture, they choose the analytics solution that enables enterprise-ready security features.
The Innovator needs a modular data stack more than anything else. A key benefit of adopting a modern stack is flexibility – adjusting and iterating as your business and technology trends evolve. You will want to stay on top of the latest tech, discerning what is hype and what can truly make a difference. Easier said than done! A few considerations…
- Your stack should be easy to pivot and change, shifting with the fast-moving needs of the business.
- Suggest solutions that integrate with legacy systems while offering flexible options for where you store, process, and analyze data into the future. How can you ensure you’re delivering a consistent experience as your stack evolves and your data moves between on-prem and cloud environments?
- You will be wise to avoid adopting too many fragmented, disjointed tools (a common pitfall for Innovators focused on shiny new best-of-breed products), lest you end up with too many overlapping point solutions.
The Innovator will likely also lead the AI implementation charge, so you will want to look for tools with a responsible framework for generative AI across the data stack.
The Transformer is on a modernization journey. Full stop. Like a captain turning a cruise ship, you must guide the business through change on a massive scale. You will lead cloud adoption to future-proof the business while managing current IT needs and legacy deployments. As a result, the Transformer will likely run a hybrid data stack. You’ll need to find platforms that work well across environments, like a SaaS-native analytics tool that connects seamlessly to an on-premises data center. You may want a desktop analytics tool that runs seamlessly in the cloud. The Transformer knows that flexibility is a must so that hybrid compatibility will win the day.
It’s worth mentioning we didn’t pull these four CIO archetypes out of thin air. You’ve likely encountered one or more of them in your own working life, IT leaders of a particular type – or on a certain mission – who were able to align their stack with their leadership style. The business world is full of terrific success stories with a variety of data stacks. Here are four such examples from within the Alteryx customer orbit.
BODi Fitness used Alteryx and the Snowflake Data Cloud to centralize data and better view the customer journey. It helped them break down silos and empower the people closest to the data, facilitating the marketing team’s analytic insights with a business domain-driven approach. The results included a 240X improvement in query performance, a 25% increase in subscribers, and 33% savings in data infrastructure costs.
Bank of America, which operates in the highly regulated financial services industry, needed to automate their largely reactive regulatory testing processes. They needed a platform that could connect to a large volume of data, and that had a simple UI anyone could use. They built an automated data ecosystem that included Alteryx Designer Cloud for data engineering and a combination of Tableau, Qlik, and MicroStrategy for visual analytics. The resource savings were significant, as were the savings in test development times.
London North Eastern Railway is always pushing the envelope in the fast-paced world of passenger trains. The team wanted to move from manual spreadsheet analysis to richer visuals and faster insights. First, they adopted Tableau to ramp up visualization and make insights more accessible. Then, when they needed deeper insights, they used Alteryx to process large volumes of data, handle different data types like IoT sensor data, and tackle their most complex analytical challenges – taking on business use cases that are cutting-edge for the rail industry.
Nielsen had to transform its legacy BI process, and it had to transform fast. Why? Because their next-day reporting process was built on a system scheduled for sunset within 90 days. They needed a complete process reboot, turning to Alteryx and AWS to build the new stack that would scale the use of analytics across their organization.
I encourage IT leaders reading this to reflect on a few questions before moving on. Who are you as a leader? What culture are you building? What are your most pressing business needs? And are you making the right data stack to meet the moment? I certainly hope your last answer was yes! Best of luck to you. I’ll leave with this call to action: to take our analytics maturity assessment for an objective view of where you are in your analytics journey and what’s needed to get you to the next stage.