AI readiness check

Is your
production company
ready for AI & Data
Analytics?

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  • 0 - 40‰A strong foundation is essential for AI success
    [Name], your score of [Score] shows that AI is still in its early stages at [Company]. That’s to be expected: without a solid digital infrastructure, including well-organized data, automation, and real-time insights, AI often remains an unfulfilled promise.

    Yitch specializes in helping companies build this foundation. We set up the right digital framework to ensure AI becomes both feasible and valuable.
  • 40 - 60‰AI adoption is underway. Is your approach ready to scale?
    At [Company], a score of [Score] indicates promising AI initiatives. The key question is whether your data is structured and reliable enough to support informed decisions at scale. Many organizations get stuck in pilot phases without translating AI into lasting business impact.

    We help bridge that gap by streamlining data processes, implementing predictive analytics, and developing AI strategies that deliver real, measurable outcomes.
  • 60 - 80‰AI is delivering results. Now it’s time to unlock its full potential
    With a score of [Score], [Company] has established a strong AI foundation. The next step is to leverage AI for real-time predictive insights, optimizing production and proactively preventing downtime.

    Yitch supports companies in scaling AI beyond proof-of-concept, turning automation and data intelligence into true competitive advantages.
  • 80 - 100‰Leading the way with AI? It’s time to maximize its impact
    With [Score], [Company] is clearly ahead in AI adoption. The focus now is on continuous improvement and driving growth through AI. What will the next milestone be?

    From predictive maintenance to autonomous processes and peak operational efficiency, Yitch offers not only expert advice but also hands-on implementation to ensure your AI strategy stays at the forefront.

Contacteer Yitch

Discover how well prepared your company is for data-driven decision-making and gain a better view of opportunities to optimize your data strategy.

Rank the answers from most important at the top to least important for your organization at the bottom.
Pick one option
Select all applicable options
Koen De Borle

Contact our Yitch business lead Koen for a more in-depth look at optimizing your data.

 

0494 05 36 38koen.de.borle@yitch.eu

Interested in how we can optimize your data?
Check here our service model.

What are the biggest challenges your company is facing right now?

Chapter one: Data infrastructure at a glance

Rank the answers from most important at the top to least important for your organization at the bottom.

  • Lack of real-time insights into production
  • Inefficiencies in production process (from raw material to packaging)
  • Inconsistent decision-making
  • Difficulty predicting market trends
  • Other¥Specify

On what basis do you currently make important business decisions?

Chapter one: Data infrastructure at a glance

Pick one option

  • Primarily based on intuition and experience‰0
  • Based on static reports (e.g., Excel, PDFs)‰2
  • With real-time dashboards and analytics‰3
  • With AI-driven recommendations‰5

Which of these problems are you currently facing?

Chapter one: Data infrastructure at a glance

Select all applicable options

  • Unplanned machine downtimes
  • Inefficient processes
  • Inadequate quality control
  • No real-time insights into production performance
  • A knowledge gap arises, e.g. because of employees leaving
  • Energy consumption
  • Other¥Specify

What % of maintenance activities go to unplanned downtime?

Chapter one: Data infrastructure at a glance

Pick one option

  • 0% - 10%‰2
  • 10% - 40%‰1
  • 40%‰0
  • No idea‰0

How/where is your company's most important data stored?

Chapter two: Data infrastructure and architecture

Select all applicable options

  • Spreadsheets (Excel, Google Sheets)‰1
  • Local databases‰2
  • Cloud storage (AWS, Azure, Google Cloud)‰4
  • We do not have a structured data storage system‰0

What tools are used to visualize your data?

Chapter two: Data infrastructure and architecture

Select all applicable options

  • Power BI‰2
  • Tableau‰2
  • Excel‰1
  • Custom dashboards‰2
  • None‰0

Is the OEE visualized?

Chapter two: Data infrastructure and architecture

Pick one option

  • Yes‰2
  • No‰0

To what extent are your data sources centralized?

Chapter two: Data infrastructure and architecture

Pick one option

  • Not at all - data is locked in different systems‰0
  • Partially - we can combine data manually if needed‰1
  • Fully integrated - we have a central data platform‰3

How often do you experience data quality problems (e.g., missing, duplicate or inconsistent data)?

Chapter two: Data infrastructure and architecture

Pick one option

  • Rarely (less than or once per quarter)‰1
  • Occasionally (at least once per quarter)‰1
  • Frequently (more than once per quarter)‰1
  • We do not monitor data quality‰0

To what extent do you use data to analyze performance and/or make decisions?

Chapter three: Data decision making and strategy

Pick one option

  • Not at all - we do not use data for decision-making‰0
  • Basic - we use reports and dashboards to track performance‰1
  • Advanced - we use predictive analytics or AI models‰2
  • Leading - AI is integrated into our business processes‰3

Has your company already implemented AI applications in operations?

Chapter three: Data decision making and strategy

Pick one option

  • No, but we would like to explore this
  • No, we do not think this is relevant to us
  • Yes, but only to a limited extent
  • Yes, and AI plays a key role in our decision-making‰1

Does your company have a clear vision regarding the use of data and AI?

Chapter three: Data decision making and strategy

Pick one option

  • No, we do not have a formal data strategy‰0
  • We have started to develop it‰1
  • Yes, but we need specialized knowledge to develop it further‰1
  • Yes, and we are actively implementing the strategy‰2

Suppose you were to implement AI and digital transformation projects in your company, which do you think are currently the biggest obstacles to implementation? (Select all applicable options)

Chapter three: Data decision making and strategy

Select all applicable options

  • Lack of data infrastructure
  • Data quality issues
  • Limited internal expertise
  • Budget constraints
  • Uncertainty about Return on Investment

Are you interested in further advice on how to improve your data and AI strategy?

Chapter three: Data decision making and strategy

Pick one option

  • Yes, I want to know more about this and identify the possibilities in more concrete terms
  • Maybe, I need more information
  • No, we are not ready for this yet
Parse
Data infrastructure at a glance

Chapter one: Data infrastructure at a glance

Data infrastructure and architecture

Chapter two: Data infrastructure and architecture

Databesluitvorming en strategie

Chapter three: Data decision making and strategy

Next Steps

Chapter four: next steps

Totaalscore

Let's go!
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