You can take ChatGPT’s word for it. Or read this post to learn about the connection between successful transformations and strong analytics maturity on display at OPEX Week 2023.
Held in Miami on January 30-February 1, 2023, OPEX Week touts itself as the “world’s no.1 OPEX and Business Transformation Event.” Based on the quality of the presentations and the caliber of attendees, I would agree.
OPEX Week Banner
Three sessions, in particular, stood out.
One was, “The Real Data Pitfall — Linking Strategy Formulation Intricately to the Insight Drawn from Datasets,” delivered by the Head of Business and Enterprise Apps at Uber, Parul Saini, that highlighted departmental insights powered by data at Uber. What’s less visible are the four capabilities underpinning it all: complete views of employees, consumers, business units and “security posture.”
From Uber’s Head of Business and Enterprise Apps, Parul Saini
This last one is notable given the nature of Uber’s business, dependency on data, and the necessity to properly secure and govern that data.
She paints a picture of analytics maturity improvement through Uber’s lens as a digital native company with “Democratized data driven innovation with deep AI expertise” and an “Agile culture” with “end to end solution ownership.”
From Uber’s Head of Business and Enterprise Apps, Parul Saini
Among the attributes of digital natives you often find are “data products” — assets with monetary value built upon data. For Uber, a good example is Michelangelo, “an internal ML-as-a-service platform that democratizes and optimizes the scaling of AI, ML and Deep Learning.” Savvy non-digital natives have learned to do the same, like Deep Brew at Starbucks.
Funny enough, ChatGPT reports that Alteryx, “enables Starbucks to gain valuable insights into customer behavior and preferences, optimize marketing campaigns, and make informed business decisions.”
See A Better Way to Put Your Data to Work from the July/August 2022 edition of the Harvard Business Review for more on this topic: “Companies that treat data like a product can reduce the time it takes to implement it in new use cases by as much as 90%, decrease their total ownership (technology, development, and maintenance) costs by up to 30%, and reduce their risk and data governance burden.”
Among Alteryx customers, Amway is a good example of how analytic workflows developed for supply chain are re-used to speed time to value for financial analysts and others. Re-usability is a key value scaler of analytics platforms.
If you were curious, Alteryx plays an important role within Uber by helping the company “make informed decisions and improve operational efficiency” with “data analytics, predictive modeling, and real-time reporting.” Thank ChatGPT once again.
Another session from Michelin showed similar ideas unfolding in a company best described as the opposite of a digital native — more old economy manufacturer (founded in 1889).
In a special closed door session, the Chief Transformation Officer Summit, Michelin’s Chief Digital Officer Romina Guevara shared the wisdom of striving to improve data and analytics maturity.
Michelin’s Chief Digital Officer Romina Guevara
She presented a 5 stage model, with most organizations falling into the green or yellow zones, short of the ideal state where “data plays a central role in as many decisions as possible.”
You can see how this unfolds in Michelin below, with a foundation similar to Uber’s in spirit, but supporting use cases unique to a manufacturer. Note the “Design and testing” workstream and mention of a digital twin. That’s a use case similar to one you find at Alteryx customer McLaren Racing.
The dimensions of Michelin’s data and analytics strategy from Chief Digital Officer Romina Guevara
Like many organizations presenting at the conference, Michelin finds Alteryx an indispensable part of their strategy. Calling once again to ChatGPT, “Alteryx helps Michelin streamline and automate various data processes, enabling faster and more accurate data analysis and insights. This can help Michelin make informed decisions, improve operational efficiency, and drive business growth.”
The last session I will highlight was delivered by Alteryx Chief Transformation Officer Steve Brodrick. I was fortunate to attend the conference with Steve and also Russ Mills, Alteryx Field CFO.
Like Romina Guevara, Steve presented in the Chief Transformation Officer Summit. A term mentioned multiple times throughout the conference was VUCA — notably for me, mentioned earlier in an excellent session by Charles Brandon, Director of the Army Business Process Improvement Program Office of the US Army.
VUCA stands for volatility, uncertainty, complexity, and ambiguity — challenges that Chief Transformation Officers can lead their organizations past by supervising the changes and improvements necessary to deal with ever-shifting and changing dynamics.
Steve’s session was about the opportunity to overcome VUCA and recommendations to come out the other side in far better shape by improving analytics maturity.
As a Chief Transformation Officer himself (with Alteryx now, but with Alteryx customer Stanley Black & Decker just prior), Steve knows the impact that transformation leadership can have on analytics improvements that lead to big time top and bottom-line results. As he said, “it represents an incredible opportunity for transformation leaders to step up.”
Alteryx Chief Transformation Officer Steve Brodrick
That first step requires benchmarking the current state to begin charting a path to continuous improvement. You can also take the Analytics Maturity Assessment and see how your organization compares with others.
If like many, you land in the spot highlighted by Steve (stage 1 or 2), you have a way to go. The good news is you can immediately start plotting a confident path forward. Made easier now with the Alteryx Analytics Cloud.
With the well-known capabilities of Alteryx now offered in the Cloud, barriers to adoption and utilization of the past fall to levels that make a journey up the maturity curve relatively easy. Considerations like provisioning users, accounting for more use cases (machine learning, interpretive BI), governance, and security, means the team can focus more on business improvement than administering technology.
Lastly, if there’s any doubt
Business or Public Sector leaders in transformation or operational excellence roles that have yet to embrace the opportunity to bring forward analytics maturity in service of your objectives should check out the following:
- McKinsey: The role of the chief transformation officer
Their mandate — responsibility for ensuring that the full bottom-line target gets delivered — must be clearly defined at the outset.
The CTO is a high-level orchestrator of a complex process that involves large numbers of discrete initiatives. Responsibility for making the day-to-day decisions and implementing those initiatives lies with line managers, but the CTO’s job is to make sure the job is done. This is not always easy. - McKinsey: Setting aspirational targets
One of the most important steps in a transformation is the choice of a financial target. Done well, that exercise sets the tone for the whole program, fundamentally changes the way people think, and liberates leaders to achieve the unachievable.
When companies set targets, we recommend starting with what’s theoretically achievable and adjusting this figure downward only when there’s clear evidence that certain actions are unrealistic.
Takeaway
These two McKinsey pieces illustrate the value of knowing your analytics maturity, precisely measuring the baselines targeted for improvement, and consistently tracking progress. To those ends, Alteryx can be a key enabling partner in your transformation journey. I will leave you with a few links to explore:
- The Alteryx Business Use Case Discovery Guide (identify and prioritize opportunities well suited to how Alteryx addresses speed, efficiency, improvement, and net new use cases)
- The Alteryx Analytics Cloud offers a capability called Metrics Store, which allows “business units to have a common language and drill down into key metrics using pre-defined business logic and standardized dimensions.” Beyond the technical explanation, Metrics Store solves a problem many leaders have measuring progress toward strategy in a consistent way up and down the organization. It’s become cliché to say it, but you cannot manage what you cannot measure. An essential enabler of any successful transformation is having everyone on the same page with the numbers.