AI for Decision Making

Decide from evidence, not from the loudest voice.

Most companies have dashboards nobody acts on.

AI for Decision Making is for business owners, heads of function and senior managers. You write one real decision as a set of questions, pick the data that answers them, set a threshold and name the person who decides.

What you’ll learn

Decisions, not dashboards: Test every metric: what would you do differently if this number doubled tomorrow?
Specify the decision: The question, the data, the threshold, the owner and the review date.
Avoid the attribution trap: Ask whether a result happened because of you, or would have happened anyway.
Build a decision calendar: Put each decision on the right clock: weekly, monthly or quarterly.
Know when not to use AI: If a person carries the consequence, a person should make the call.

What you’ll do

Name the decisionShare one decision you are avoiding because you don’t trust the numbers behind it.
Test your metricsAsk what you would do differently if a number doubled tomorrow. If the answer is nothing, delete the metric.
Write one live decisionSet out the question, the data, the number at which you act, the owner and the review date.
Check with a partnerSwap with a partner, who checks whether your trigger is a real number or just a feeling.
Work through the attribution trapUse an advertising example to separate results you caused from results that would have happened anyway.
Place it on the calendarDecide whether your decision belongs in a weekly, monthly or quarterly review.
Check where AI doesn’t belongLook for decisions that are irreversible, one-off or missing data, or where a person carries the consequence.
Make your commitmentRead one sentence aloud: the decision you will stop avoiding, and the date you’ll decide by.

What you’ll leave with

One real decision, fully written out
A clear number at which you will act
One named owner and a review date
A place for the decision on your calendar
A dated commitment to decide

An example workflow

Comparing suppliers before a decision

A team has three supplier proposals and a deadline. Prices, features and contract terms are set out differently in each one.

Upload the proposalsThe three proposals are shared with an AI assistant.
Ask in plain EnglishThe request is simple: “Compare these side by side and flag hidden fees, risky contract terms and missing features.”
AI builds the comparisonIt creates one spreadsheet covering price, features and contract terms.
AI suggests questionsIt lists what to ask each supplier about the gaps it found.
A person makes the callThe owner checks the numbers, speaks to the suppliers and decides.

AI organizes the evidence. A person makes the call.

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Questions

All questions

What does SDR do?

SDR is a learning consulting company. We help companies adopt AI, starting with training. When you’re ready, we can also work alongside your team to build what you need.

Why start with training?

AI adoption depends on people, not software. Training helps your team see what AI can do for them and try it on their own work. That is what turns a tool into a new way of working.

Will AI make decisions for us?

No. AI can help you find better evidence, but if a person carries the consequence, a person should make the call.

Do we need perfect data first?

No. You start with a real decision and work out what data it needs. If that data doesn’t exist yet, you’ll know what to fix.

Is this a course on dashboards?

No. It is about making decisions. A dashboard only matters if it changes what you do.

Can SDR help us implement what we learn?

Yes. Through Embedded AI Engineering we design, build, integrate, test and deploy with your team, subject to scope and technical requirements.

How do we get started?

Tell us your goals, your team’s experience and the challenges you want to address. We’ll suggest the right program or mix of services.

Let’s put AI to work.

Tell us your goals and your team’s experience, and we’ll shape the right next step.

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