11 QUESTIONS

People. Data. Technology.

Pick the answer that best matches your organization.

PEOPLE

1 How involved is management in data-driven decision making?

Actively involved, data is central to decisions

Aware of AI possibilities, but doesn't know how to take concrete steps

Mixed, some departments yes, others no

Limited, data is rarely discussed at management level

Not at all, decisions are mainly based on gut feeling

2 How many critical processes depend on specific individuals?

Almost none, processes are well documented

A few processes, but there is knowledge overlap

Multiple processes, holidays or illness are noticeable

Many processes, absence directly leads to problems

Almost everything, the organization runs on individual heroes

3 How do employees handle new digital tools or ways of working?

Enthusiastic, employees actively seek improvements

Positive, but they need guidance

Mixed, some embrace it, others resist

Reluctant, changes meet resistance

Very reluctant, every change is a struggle

4 How much AI and data knowledge exists in your organization, and are there plans to strengthen it?

We have a data or AI team and invest structurally in knowledge

Some people have knowledge, and we have plans to expand it

Limited knowledge, we are exploring but have no concrete plan yet

Almost no knowledge, the topic is not on the agenda

No knowledge and no plans, we don't know where to start

DATA

5 How would you describe the data maturity of your organization?

Data is a strategic asset, we invest in it structurally

We have the basics in order, but lack coherence between departments

Data is maintained per department, but there is no overarching view

Data is a byproduct of processes, nobody is responsible for it

We don't really know what data we have and where it is

6 How reliable is the data your organization bases decisions on?

Reliable, we have a single source of truth

Mostly reliable, occasional discrepancies

Mixed, it depends on the system and department

Unreliable, we always check manually

Nobody knows which data you can trust

7 In how many different systems is your business-critical data stored?

1-2 systems, well integrated

3-4 systems, some integrations

5-7 systems, limited integration

8+ systems, data is scattered everywhere

We don't know exactly how many systems contain data

80% of AI projects fail. This scan shows you why, before you invest.

8 How much time does it take to compile a reliable management report?

Minutes, it's mostly automated

Less than an hour, with some manual work

Several hours, data must come from multiple sources

Half a day or more, lots of manual work

Reports take hours and nobody trusts the conclusions

9 How quickly do you have insight into operational problems?

Real-time, we have dashboards and alerts

Same day, but it takes some effort

Within a few days, after manual analysis

Often too late, problems only surface when things go wrong

Shortages only become visible when the customer calls

TECHNOLOGY

10 How many manual steps are in your core processes (quotes, orders, invoices)?

Minimal, most processes are automated

Some manual steps, but it works

Lots of manual work, but it's routine

Too many, it structurally costs time and leads to errors

Quotes take too long, invoices don't match, errors are daily

11 How quickly do quality issues become visible in your organization?

Proactive, we detect trends before problems arise

Quickly, within hours of occurrence

Usually same day, sometimes later

Often too late, complaints are the first signal

Quality issues only become visible after the fact

12 How is AI and data policy organized in your organization?

Clear policy, sanctioned tools, data stays internal

General policy, but not everyone follows it

No policy, employees use whatever they want

No policy and no awareness of the risks

Data has already been shared outside via public AI tools

YOUR RESULT

0/60

YOUR PROFILE

People. Data. Technology.

0/20

People

0/25

Data

0/15

Technology

YOUR TOP FRICTIONS

Where the biggest risks are

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Is your organization ready for AI?

People. Data. Technology.

People. Data. Technology.

People

Data

Technology

Where the biggest risks are

Want the detailed analysis?

Your analysis is on its way

Want to know what your frictions cost?

Or talk to Pieter directly