1Welcome
2Context
3Value domains
4Options
5What do we need?
6In conclusion
ADC × Stage Entertainment
AI-Powered
Show Planning
A proposal for data-driven decision making
Context

Ready to explore how Stage Entertainment can drive better, data-based decisions

Trend

Smart decisions in live entertainment

Data Science and AI are becoming standard tools for theatre producers to plan seasons and runs more intelligently.

  • Producers use data and AI to forecast demand per title, city and performance time.
  • This supports smarter decisions on run length, show mix, seat categories and pricing.
  • Stage Entertainment already has rich ticketing and marketing data that can fuel these models.
Challenge

Fragmented, intuition‑driven decisions

Stage Entertainment still relies strongly on local experience and Excel to steer big production decisions.

  • Country teams work from their own views, making portfolio‑wide comparisons difficult.
  • Decisions on extensions, transfers and closures can be slow and heavily discussion‑driven.
  • There is no single, shared quantitative view that all stakeholders can trust for scenario planning.
Opportunity

Evidence-based production & run optimisation

By turning data into forward‑looking insights, Stage Entertainment can orchestrate its portfolio more objectively.

  • An AI solution can forecast demand per show, city and week, and simulate alternative scenarios.
  • Local and central teams get one shared view of expected performance across all theatres.
  • This enables faster, better‑aligned decisions on which show plays where, when and for how long.

Ready to explore how Stage Entertainment can drive better, data-based decisions?

Three domains that generate exceptional value together

Every engagement starts with Design thinking to frame the challenge. From there, Technology and Science run in parallel, coming together as an integrated, data-driven capability for Stage Entertainment.

Design
Click to explore
Technology
Click to explore
Science
Click to explore
Data-driven
Stage Entertainment
Value Domain 01, Design Thinking

Design

The Challenge
What we're solving

Most AI projects fail not because of bad technology, but because they solve the wrong problem.

Stage Entertainment needs clarity on which decisions to improve before investing in models and data pipelines.

Without a design phase, even the best algorithms end up solving a problem nobody actually has.

→
The Approach
How we solve it
1
Frame

Run workshops with planners, creatives and local directors to map where data can genuinely change decisions.

2
Design

Work with our in-house design studio CLEVER°FRANKE to turn insights into clear concepts and prototypes that all teams can understand.

3
Validate

Test concepts with real users before any engineering starts, so the final product is built on solid ground.

→
Why it matters to Stage Entertainment
The impact for Stage Entertainment
1

Ensures we solve the right problems first, aligned with visitors, creatives and local markets, not just what the data happens to show.

2

Turns abstract analytics into clear concepts and prototypes that commercial, creative and operations teams can all understand and buy into.

3

Increases adoption: shows, tools and dashboards are designed around the daily reality of theatre teams, so people actually use them.

Value Domain 02, Data & AI Engineering

Technology

The Challenge
What we're solving

Stage Entertainment has data across ticketing, marketing and operations, but it lives in separate systems across countries.

Without a connected, trusted data foundation, AI models cannot run reliably or at scale.

Non-technical teams have no self-service way to access insights, making the organisation dependent on a small group of data specialists.

→
The Approach
How we solve it
1
Audit

Assess the existing Azure & BigQuery setup to map data sources, quality and gaps.

2
Build

Design and implement a scalable data architecture that connects all relevant data across countries and theatres.

3
Deploy

Deliver GenAI-powered tools and an AI Cockpit in your cloud environment, with monitoring and governance in place.

→
Why it matters to Stage Entertainment
The impact for Stage Entertainment
1

Provides a robust Azure / BigQuery‑based foundation so data from ticketing, marketing and operations can be trusted and combined across all countries and theatres.

2

Enables GenAI and analytics products (e.g. an "AI Cockpit") that give non‑technical users fast, self‑service insights for programming, pricing and marketing.

3

Scales AI solutions from one pilot production to the full portfolio, without fragile one‑off tools or manual workarounds.

Value Domain 03, Data Science & Causality

Science

The Challenge
What we're solving

Shows compete with streaming, gaming and live events, as audiences are price-sensitive and have more alternatives than ever.

Traditional models conflate correlation with true price sensitivity, making revenue optimisation guesswork.

Inaccurate elasticity estimates leave seats unsold or revenue behind, eroding production margin.

→
The Approach
How we solve it
1
Analyze

Model booking data to estimate elasticity per show, market and tier.

2
Hypothesize

Formulate testable pricing ideas grounded in data signals.

3
Test

Run multi-arm pricing experiments to validate and refine.

4
Integrate

Feed causal results back to sharpen every future forecast.

→
Why it matters to Stage Entertainment
The impact for Stage Entertainment
1

Stage can optimise ticket prices by show, city and tier, filling houses without sacrificing revenue.

2

Every pricing decision becomes evidence-based, not gut feel or competitor benchmarking.

3

Each production's learnings compound into a durable pricing advantage that grows with every show.

Option I
Demonstrate value quickly and pragmatically
6 weeks · 2 consultants
→
Option II
Converting science and technology into tangible business impact
10 weeks · 2–3 consultants
Recommended
→
Option III
Embed and deploy 2 use cases into business solutions
12 weeks · 2–3 consultants
→

Demonstrate value quickly and pragmatically

Roadmap
Scan
Solution design
Proof-of-concept
Start
Success6w
Design Science
What we do
  • Week 1 – Scan
    • Run a kickoff scan to deeply understand the Show Planning challenge and how it shows up in day‑to‑day decisions.
    • Map Stage Entertainment's IT landscape (Azure & BigQuery setup, data sources, integrations) to identify what's available for the Proof-of-Concept.
  • Week 2 – Solution Design
    • Define the solution space: what the Proof-of-Concept deliverable will look like and how it fits in the planning workflow.
    • Align with stakeholders on functional scope and success criteria, without locking in mathematical or modelling choices yet.
  • Weeks 3–6 – Proof‑of‑Concept Build
    • Build the model in a sandbox or local environment.
    • Hand over the Proof-of-Concept to your team, including a clear walk‑through of results, limitations and a roadmap towards a production‑ready solution.
Team

A core team of two ADC consultants works on this project, together with designers from CLEVER°FRANKE.

ManagerADC
40 hrs / week
Experienced delivery manager with both technical and consulting expertise.
ConsultantADC
40 hrs / week
Technical expert in data and software engineering.

Standard core team from ADC, backed by embedded senior QA and flexible ADC expertise to guarantee delivery.

What you get
  • In 6 weeks, a validated Proof-of-Concept that shows whether AI can meaningfully improve one part of Show Planning.
  • A clear view of data readiness and model performance for this use case, including limitations and risks.
  • A short implementation roadmap describing what is needed to turn this Proof-of-Concept into a production‑ready solution.
  • Low‑risk way to create internal buy‑in for AI in planning before making larger investments.
Investment
€92.200
Excl. VAT · Medium support from Stage Entertainment

Converting science and technology into tangible business impact

Our recommendation to start with based on the initial outreach
Roadmap
Technology Science
Scan
Solution design
Build & test
Build & test
Start
Decide2w
Success10w
Design Technology Science
What we do
  • Week 1 – Scan
    • Run a kickoff scan to deeply understand the production planning challenge and how it shows up in day‑to‑day operations.
    • Map Stage Entertainment's IT landscape (Azure & BigQuery, data sources, integrations) to identify what we'll build on.
  • Week 2 – Solution Design
    • Define the solution space: what the planning engine deliverable will look like and how planners will use it day‑to‑day.
    • Align with stakeholders on functional scope and success criteria, without locking in mathematical or modelling choices yet.
  • Weeks 3–10 – Build & test
    • Build the AI planning engine and connect it to the agreed data sources.
    • Develop a simple, usable interface or integration for planners (e.g. dashboards, exports).
    • Test and validate the solution in your test and/or acceptance environments, with iterative feedback from planners.
Team

A core team of two or three ADC consultants works on this project, together with designers from CLEVER°FRANKE.

ManagerADC
40 hrs / week
Experienced delivery manager with technical and consulting expertise.
ConsultantADC
40 hrs / week
Technical expert in data and software engineering.
DeveloperADC / Stage
40 hrs / week
Technical expert in data and software engineering, staffed by ADC or Stage.
*Either ADC or Stage Entertainment developer, or combination of two profiles.

Standard core team from ADC, backed by embedded senior QA and flexible ADC expertise to guarantee delivery.

What you get
  • In 10 weeks, one production‑ready prototype of an AI planning engine that has been tested within your own environment already.
  • A future‑proof architectural foundation on Azure/BigQuery designed to host additional AI use cases later.
  • Practical knowledge transfer to your internal data/tech team so they understand how to operate and extend the engine.
  • A concrete, objective tool that planners can use immediately to steer decisions and improve overall turnover.
Investment
€185.700
Excl. VAT · Amount can change, depending on the level of technical support Stage Entertainment provides.

Embed and deploy 2 use cases into business solutions

Roadmap
Technology Science
Scan
Solution design
Build, test and deploy
Build, test and deploy
Start
Decide2w
Success12w
Design Technology Science
What we do
  • Week 1 – Scan
    • Run a kickoff scan to deeply understand the planning challenge and how it shows up across central and local teams.
    • Map Stage Entertainment's IT landscape (Azure & BigQuery, data sources, integrations) so both solutions can integrate cleanly.
  • Week 2 – Solution Design
    • Define the solution space: what the AI cockpit and the planning engine should look like and how they fit in the broader planning workflow.
    • Align with stakeholders on functional scope of both solutions and how they share inputs/outputs, without locking in mathematical or modelling choices yet.
  • Weeks 3–12 – Build, test & deploy
    • Build the AI cockpit and the planning engine, and integrate them end‑to‑end with your cloud data pipelines.
    • The AI cockpit lets central and local teams compare scenarios across the entire portfolio, while the planning engine drives the underlying optimisation.
    • Deploy both solutions in production with robust monitoring, governance and hand‑over to your internal teams.
Team

A core team of two or three ADC consultants works on this project, together with designers from CLEVER°FRANKE, but operating over a longer period with a broader scope for maximum impact.

ManagerADC
40 hrs / week
Experienced delivery manager with technical and consulting expertise.
ConsultantADC
40 hrs / week
Technical expert in data and software engineering.
DeveloperADC / Stage
40 hrs / week
Technical expert in data and software engineering, staffed by ADC or Stage.
*Either ADC or Stage Entertainment developer, or combination of two profiles.

Standard core team from ADC, backed by embedded senior QA and flexible ADC expertise to guarantee delivery.

What you get
  • In 12 weeks, two production‑ready solutions, an AI cockpit and a planning engine, giving a portfolio‑wide view on what, where, when and how long.
  • A robust, scalable architecture proven to handle multiple models and ready for additional AI use cases.
  • Deep capability transfer to your internal teams, embedding advanced AI planning into the organisation instead of a one‑off pilot.
  • A powerful, integrated toolset that supports strategic portfolio optimisation, not just isolated planning decisions.
Investment
€225.840
Excl. VAT · Amount can change, depending on the level of technical support Stage Entertainment provides.
What do we need?

What we need to discuss before we can start

Legenda
1Option 1
2Option 2
3Option 3

Depending on the chosen path, ADC applies a set of entry criteria that must be in place for the project to succeed.

Tech resources

Stakeholders

Developer Tooling
→
Approved access to AI coding agents to accelerate development velocity
123
Business or Product Owner
→
Defines value, approves scope and success metrics
12
→
Accountable for live business impact, ROI, and ongoing operations
3
Target Environment
→
Isolated sandbox available with access to approved GenAI resources
1
→
T/A environments available with access to approved GenAI resources
2
→
Full production environments available with access to approved GenAI resources
3
End-user representatives
→
Available for user testing and feedback
1
→
Available for user testing, feedback and adoption preparation
2
→
Available for user testing, feedback and full operational adoption
3
Access & Permissions
→
Basic access in place (named users, temporary data access)
12
→
Strict access in place (least-privilege, secure connections)
3
Risk & Compliance
→
Light-touch review for safe sandbox use
1
→
Test/Acceptance sign-offs and ongoing compliance review
2
→
Final production sign-offs and ongoing compliance monitoring
3
Data Availability
→
Static data extracts or synthetic data approved for testing
12
→
Depending on the use-case: live data connections established or static production-data available
3
CISO / Security
→
Secure design, access, approvals
1
→
Secure design, access, T/A approvals
2
→
Secure design, access, live production approvals
3
Resource Groups
→
Dedicated resource groups established
23
Data Owner or Steward
→
Data permissioning
12
→
Live data governance and ongoing quality ownership
3
DTAP Readiness
→
Test/Acceptance environments available (from week 3 onwards)
2
→
Fully automated CI/CD pipeline ready for live deployments (from week 3 onwards)
3
IT / Platform & Architecture
→
Assists with initial sandbox provisioning
1
→
Ensures alignment with integration constraints and DTAP standards
2
→
CI/CD integration, deployment architecture
3
Note: All environments and tooling must comply with Stage Entertainment security & compliance standards.
Availability Requirement: All stakeholders above are available approx. 2 hours/week for check-ins, sign-offs to avoid delays, and handover sessions.
In conclusion
Let's build the
future of Show
Planning together.
ADC brings together design, technology, and science to give Stage Entertainment a genuine, mathematically grounded competitive advantage in show planning and revenue optimisation.
Your contacts at ADC
Edward Jansen
Edward Jansen
Principal, ADC
Casper Wichers
Casper Wichers
Senior Consultant, ADC
Juliette Makau
Juliette Makau
Senior Consultant, ADC