How Data and AI Can Change Business Decision-Making
FIG. 01 · From strategy in Playing to Win to using data and AI to support decisions.
For me, using data and AI in business should begin with the decisions we are responsible for.
How much more inventory should we carry? Which customers should we prioritise? And after we invest, will the business still have enough cash to keep moving?
Put information where decisions happen
In Redefining Work with Data and AI, Anahita Tafvizi describes how Snowflake began using AI internally to help its sales team access knowledge and information scattered across different sources.
That work expanded into a Go-to-Market agent, which she reports was handling more than 30,000 questions a week. Read the original article
What interests me is how information becomes part of the moment when people are doing their work, through tools they already use, such as Slack and Salesforce. This brings information closer to the decision.
The question volume tells us about adoption.
To understand the business value, we still need to examine whether it saves time or changes the outcomes of decisions. Snowflake's internal use case
FIG. 02 · Conceptual illustration of the Snowflake case described by Anahita Tafvizi.
Let strategy guide the information you need
This connects with Playing to Win by A.G. Lafley and Roger L. Martin. Once we choose where to compete and how to win, we need the capabilities and management systems that support those choices.
I see data and AI as part of the capabilities we need to design around our business strategy. Roger Martin's explanation
FIG. 03 · Where you compete and how you win shape the information and management systems you need.
Inventory connects opportunity with cash
Consider a hypothetical inventory replenishment decision. If a company competes by keeping products ready to ship for a particular customer group, it needs to consider which products matter to those customers and how stockouts could affect sales opportunities.
But adding inventory takes cash. If sales are slower than expected, that cash stays tied up for longer.
The decision therefore needs to connect sales, stock on hand, costs, delivery lead times, and the timing of cash receipts and payments.
FIG. 04 · Five types of information to bring together before replenishing inventory.
FIG. 05 · Original Business Play artwork from Power Ladder.
Consider opportunity and financial readiness together
This is the core of Business Play that I want to bring into everyday work: consider Opportunity alongside Financial Readiness, then compare the options before committing.
FIG. 06 · Calculated Ambition: weigh business opportunity alongside financial readiness.
When we design analysis around a company's data in Snowflake, we can ask AI to help assess alternatives. We might replenish every product group, or prioritise products for our target customers.
Each option needs to show the expected opportunity, the cash required, and the consequences if sales fall below our assumptions.
FIG. 07 ·
Each option needs to account for opportunity, cash commitments and sales uncertainty.
Experts make the question and criteria clear
The expert's role is to work with executives to frame the question, check what the data means, choose assumptions, and establish decision criteria.
The team also needs to understand when to use the analysis and when to revisit it with the person responsible for the decision.
FIG. 08 · Roles applied from the author's perspective in this article.
This is how I see data, AI, and experts working together in Power Ladder's Business Play.
Start with the choices facing the business. Then connect source data to the point where decisions are made, and analyse the alternatives before acting, so the work leads to meaningful outcomes.
FIG. 09 · Connect data, establish rules, compare options and follow the results.
Take the seat of a cosmetics business owner
Make decisions about stock, promotions and cash. Explore how your choices change opportunity and financial readiness.
Explore stock, promotion and cash decisions in a business simulation.
FIG. 10 · Explore the idea through a cosmetics business scenario.
Fictional scenario and draft game scores for practising decisions, not an assessment of your business.
Discuss your business with Power Ladder
Before we finish: if you started with just one decision in your company, which one should bring data, business opportunity, and financial readiness to the same table?
If you do not yet have an answer and would like us to help you find it, get in touch.
Tell us about your business and the decision you would like help with.
References and further reading
Anahita Tafvizi · Redefining Work with Data and AI ↗ Published 25 November 2025. Source for the internal Snowflake use case and the reported volume of more than 30,000 weekly questions. This is the author’s historical account, not a new measurement of current usage.
Roger L. Martin · Where’s the Business Model in Playing to Win? ↗ 22 March 2021. The author’s explanation of Where to Play, How to Win, and the capabilities and management systems that support strategy. Book: Playing to Win by A.G. Lafley and Roger L. Martin.
Power Ladder · Calculated Ambition: The Cosmetics Owner Challenge ↗ A learning experience with five decisions, a fictional scenario and draft game scores.
Comments