Decide better, faster, with data that's finally useful

Data-driven decision-making means turning scattered industrial information into reliable references for decisions rather than multiplying dashboards with no real lever for action.

Indao consolidates this data into clear, actionable references, helping teams decide faster, more accurately and with greater confidence.

Request a demo See concrete examples

Why act now

Explosion of industrial data volumes

Sensors, supervisory systems, historians… but limited real decision-making value

Decisions under operational pressure

Limited time, partial information, constant trade-offs

Indicators that are difficult to compare

Sites, lines, products or contexts are hard to benchmark

Gap between available data and actual decisions

A lot of information… but few truly data-driven decisions

These limitations are well known.

The real question is now: how can data be transformed into operational decision-making capability?

Why your current tools are reaching their limits

Supervisory and reporting tools show what is happening.
They rarely help decide what to do.

Traditional dashboards describe past consumption or performance, but provide limited insight into root causes or priority actions
Analysis often relies on individual expertise and available time, making decisions variable and difficult to reproduce
Without correlating process, energy and operational parameters, it becomes difficult to identify what truly drives deviations or yield losses
Variations in recipes, raw materials or operating conditions prevent objective comparisons without proper normalisation
Manual consolidation of data from multiple sources consumes time and often delivers reports too late to influence operational decisions

The Indao approach

Indao transforms industrial data into reliable operational references, directly usable for decision-making.

Understand before acting.
Decide based on facts, not assumptions.

What Indao does in practice

  • Multi-source consolidation (process, quality, energy, production, maintenance)

  • Automatic contextualisation of data (product, load, conditions, environment)

  • Construction of comparable, normalised indicators

  • Identification of the real performance levers

  • Detection of significant deviations and atypical situations

  • Near real-time operational decision support

STEP 1

Collect

Process, production, quality, environmental and contextual data

Indao connects and structures industrial data from multiple systems to create a consistent and usable foundation for decision-making.

STEP 2

Contextualise

Production conditions, constraints, normal variability

Data is linked to its real operational context to avoid misinterpretation and enable meaningful comparisons.

STEP 3

Structure

Comparable indicators and reliable references

Indao builds normalised indicators to compare truly equivalent situations across products, lines, time periods or sites.

STEP 4

Decide

Objective operational trade-offs

Teams gain a clear understanding of priority levers and can make decisions based on measurable facts.

STEP 5

Learn

Capitalisation and continuous improvement

Each decision and outcome feeds a knowledge base that continuously improves operational practices.

Measurable, sustainable benefits

Indao does not replace human expertise.
It makes it more reliable and faster.

Teams benefit from contextualised analyses and reliable indicators to quickly identify relevant levers and secure operational choices
By objectifying interactions between processes, resources and constraints, Indao reduces decisions driven by intuition or pressure
Production, energy, maintenance and management rely on the same performance view, avoiding conflicting interpretations
Data normalisation enables objective benchmarking despite differences in volume, recipes or operating conditions
Analyses and decisions become traceable and reusable, transforming individual experience into lasting collective knowledge
A shared understanding of causes and impacts improves coordination across teams for more consistent decisions

What is data-driven decision-making in industry?

Data-driven decision-making means using available industrial data (process, energy, quality, maintenance) to objectify operational decisions, rather than relying solely on experience or intuition. In practice, this involves consolidating scattered data, putting it into context, then building comparable indicators to identify the levers that genuinely influence performance. The goal is not to replace teams' expertise, but to give them reliable references to decide faster and with greater confidence.

Want to make decisions differently?

Let’s explore how your data can become a concrete operational lever.

Request a demo

Where we create the most impact

One platform,
industry-specific answers

  • cogeneration
  • HVAC
  • wind energy
  • green hydrogen
  • boilers

Energy

Optimise the production and use of your energy systems to improve reliability and efficiency.

  • acids
  • chemical products
  • PVC
  • industrial gases
  • fertilisers
  • plastics
  • petrochemicals

Chemicals

Improve the reliability and energy performance of your chemical processes while strengthening safety and compliance.

  • wastewater treatment
  • recycling
  • water distribution
  • waste management

Water & Waste

Optimise the management of your networks and treatment facilities, improving reliability, energy efficiency and environmental impact.

  • cement
  • steel
  • non-ferrous metals
  • mining
  • construction materials
  • glass

Minerals & Metals

Stabilise your processes and optimise energy consumption across steelmaking, cement, glass and mining operations.

  • breweries
  • dairy products
  • soft drinks

Food & Beverages

Optimise your brewing, distillation, dairy and beverage processes to reduce losses and resource consumption.

  • cnc
  • laser

Machine-tools

Ensure the availability and precision of your CNC and laser systems by anticipating deviations and unplanned downtime.

  • recycled pulp
  • paper machines
  • packaging
  • tissue paper

Pulp & Paper

Optimise yield, availability and energy performance across your pulp, paper and packaging operations.

Indao is not just a monitoring tool: it is an advanced analytics platform that transforms industrial data into concrete, actionable recommendations. Where SCADA or ERP systems collect and display data, Indao helps your teams gain clarity, take the right actions and optimise operations sustainably.

Deployment is fast and progressive. On average, 4 to 6 weeks are enough to connect your first data sources, build the models and launch the first dashboards.

The platform is modular: you can start with a targeted pilot on a critical asset, then progressively extend it to other lines, sites or countries.

Indao is designed for the entire manufacturing industry and industrial infrastructure.

The platform adapts to a wide range of sectors, processes and equipment, wherever industrial data is available.

ROI is assessed based on concrete indicators: operational performance, asset availability, energy consumption and product quality.

Indao structures the business case from the outset and enables tracking of actual gains over time.