Always be learning | FAQ

Question 1

What do you mean by 'the business doesn't start in a dashboard'?

Accepted Answer

Dashboards are a means. The goal is: better decisions, lower costs, more growth, less risk — visible in the business.

Question 2

How do you usually start?

Accepted Answer

We start with concrete business questions (operations/finance/commercial) and translate them into a short roadmap with improvements that deliver immediate value, plus a solid foundation for the long term.

Question 3

What does your framework look like?

Accepted Answer

The ABL Framework clarifies where you stand, where you want to go, and what steps are needed to increase data maturity across people, business, and tech.

Question 4

Why do you say 'you get returns from data with people'?

Accepted Answer

Because technology alone delivers nothing: value only emerges when people use data in decisions and processes.

Question 5

What do you do concretely?

Accepted Answer

We build and strengthen effective data organizations: people (team/roles/rhythm), business (questions/KPIs/use cases), and technology (platform) aligned with each other.

Question 6

What happens after the Data Impact Session?

Accepted Answer

We translate the top-3 into a roadmap and choose the right team format together (tandem/squad/team).

Question 7

Who should be present at the Data Impact Session?

Accepted Answer

Management team/core team + representation from operations, finance, or commercial (where the impact lies).

Question 8

What does the Data Impact Session deliver?

Accepted Answer

A shared problem sketch, top-3 opportunities, and a concrete first step.

Question 9

Who is the Data Impact Session intended for?

Accepted Answer

For organizations that want 'more with data/AI' but lack focus.

Question 10

When do I choose external vs internal data team?

Accepted Answer

External as an accelerator or temporary reinforcement; internal if you want to make data structurally a strategic pillar. We often help with the transition.

Question 11

What if we already have a data team but the return is low?

Accepted Answer

Then we bring back structure, priorities, and standards, and reconnect the work to business questions that matter.

Question 12

How do I develop data specialists into sparring partners for the business?

Accepted Answer

By placing them close to operations/finance/commercial, with ownership of KPIs and regular alignment with stakeholders.

Question 13

How do I build a mature data organization step by step?

Accepted Answer

Start with structure and foundation, then deliver repeatable value through use cases, and then secure governance and adoption.

Question 14

How do I make my data team more effective and efficient?

Accepted Answer

By clarifying roles, working methods, and standards and coaching until the team operates independently.

Question 15

How do I get more value from my data team?

Accepted Answer

By prioritizing business impact: one rhythm, one roadmap, and work that directly accelerates decisions.

Question 16

How do you ensure data doesn't stay in silos?

Accepted Answer

Through shared definitions and standards (reports/KPIs) and organizing collaboration across domains.

Question 17

How do I prepare my organization for data-driven work?

Accepted Answer

By arranging mandate and budget, agreeing on ownership, and choosing a technology base that doesn't hinder growth.

Question 18

How do I ensure the business sees the value of data?

Accepted Answer

By starting with their pain: where is money, time, or quality being lost — and quickly converting that into visible improvements.

Question 19

How do I build a culture where people naturally reach for data?

Accepted Answer

Through leadership + rhythm: data becomes part of decision-making, not something extra alongside the work.

Question 20

Which stack do you choose?

Accepted Answer

What fits with ambition, budget, and team — tool-agnostic, pragmatic, and only deployed if it truly adds value.

Question 21

What do you mean by data modeling?

Accepted Answer

Converting raw data into logical business language (customer, revenue, margin, etc.), so teams use the same truth.

Question 22

Do you do data migrations?

Accepted Answer

Yes, preferably step by step, so you can continue and keep delivering value during the transition.

Question 23

What do you build on the technical side?

Accepted Answer

A robust, scalable, and secure data platform, plus models and pipelines with which new questions can be answered quickly and reliably.

Question 24

Why is technology still important if it's 'about people'?

Accepted Answer

Because technology is the backbone: without a robust platform, people become slow, uncertain, and dependent.

Question 25

Can you do churn analysis / dashboards?

Accepted Answer

Yes, if it's linked to actions: who is at risk, why, and what are we going to do in sales/service?

Question 26

How do I make the impact of data visible to management?

Accepted Answer

By showing per initiative: which choice gets better, which KPI changes, and what that delivers in money, time, or risk.

Question 27

How do I make management information truly usable for the management team?

Accepted Answer

By sharpening KPI definitions, securing ownership, and linking the dashboard to the decision rhythm.

Question 28

Do you build dashboards?

Accepted Answer

Yes, but always as part of a broader approach: a dashboard is a tool to accelerate decisions.

Question 29

What is MLOps and why would I want it?

Accepted Answer

Because otherwise models become one-time projects: MLOps makes it maintainable, measurable, and reliable in production.

Question 30

Can we chat with our data?

Accepted Answer

Yes, if it's set up securely and manageably, so people actually work faster through it instead of extra noise.

Question 31

What is 'AI with data' at ABL?

Accepted Answer

AI that accelerates your data organization: better decisions, smarter processes, and use cases that land in the business (not just a demo).

Question 32

Do you build ML/AI models?

Accepted Answer

Yes, but always from a concrete business question: where are you leaving money, time, or quality on the table — and what needs to be better?

Question 33

When am I ready to deploy AI on my data?

Accepted Answer

When your data and definitions are reliable enough and your team/organization is ready to use AI outcomes in decisions.

Question 34

What do you mean by 'data teams with a permanent seat at the board table'?

Accepted Answer

That data is not a support function, but participates in discussions about direction, KPIs, and priorities — because it makes direct business impact.

Question 35

What makes you different from tech-first agencies?

Accepted Answer

We don't start with tooling, but with impact: team, decision-making, and technology that supports the work.

Question 36

What do you believe in as an agency?

Accepted Answer

That almost every modern company is fundamentally a data company — and that value only emerges when people use data to make smarter choices.

Question 37

Since when have you existed?

Accepted Answer

ABL is a growing data agency since 2020.

Question 38

Where does the name Always be learning come from?

Accepted Answer

Because for us it's about two things: data (raw material to learn from) and people (continuing to develop as a specialist, colleague, and person).

Question 39

Why does ABL suit specialists who want to grow?

Accepted Answer

Because development is not a side issue, but the foundation on which we build our work.

Question 40

Which roles are you looking for?

Accepted Answer

For example AI internship, Data consultant, Data engineer, BI engineer (depending on the moment).

Question 41

Do you work alone or in teams?

Accepted Answer

Both: you work alone or in small teams at end clients, depending on project and team format.

Question 42

What characterizes your culture?

Accepted Answer

Sharing knowledge, honest feedback, accessible collaboration, and setting the bar high — in a safe setting to try new ideas.

Question 43

What is it like to work at ABL?

Accepted Answer

You work in a close-knit group of specialists, close to the business, with room to grow and get better every day.

Question 44

Do you also do Microsoft Fabric / cloud stacks?

Accepted Answer

Yes, if that fits your situation and governance and security can be properly arranged.

Question 45

Are you tool-independent?

Accepted Answer

Yes: the goal is impact. Tooling is supportive, not leading.

Question 46

Which tools do you work with?

Accepted Answer

We know the tools and best practices, but choose pragmatically what fits your ambitions, budget, and team.

Vragen die we graag beantwoorden

ABL aanpak: Mens × Business × Techniek

Data Impact Sessie

Data team bouwen & effectiever maken

Datagedreven cultuur & adoptie

Platform, integraties & engineering

Dashboards, analyses & stuurinformatie

AI, machine learning & “AI met data”

Over Always be learning

Werken bij ABL

Tools & technologie