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Step 1: Needs Assessment

Identify your team’s actual needs to avoid unnecessary investments at an early stage.

Finding the right starting point

By carrying out a targeted needs analysis, you can safeguard your budget and ensure that the technology will make a noticeable difference to your team’s workload later on.

Before purchasing software, you should identify where the biggest bottlenecks lie in your day-to-day care work and which processes are suitable for the use of AI.

So don’t start by asking: “Which AI is the easiest to install?”

Instead, focus on the question: “Which specific problem in our organisation do we want to solve?”

Why this step determines the success of your project

AI solutions only create value when they address real challenges in day-to-day care. Without clear objectives, there is a risk of investing in technologies that fail to meet practical needs and are rejected by the team.

A successful needs assessment uncovers administrative burdens and identifies processes that cost your employees valuable time.

A needs assessment should not be conducted solely from behind a desk. Instead, it should be based on an early and systematic collection of perspectives directly from everyday care practice.

Success Factor

Successful projects start with a clearly defined use case – not with a technology.

AI is the tool, not the goal.

4 questions to guide your decision-making

Use these guiding questions in your next strategy meeting:

  • What are currently the biggest challenges in day-to-day care?

  • Where do delays, information loss, or excessive workloads occur?

  • Which routine tasks take up time that is needed for direct care?

  • What measurable goal (e.g., saving time on documentation) are you pursuing?

Gruppe von Menschen in blauen T-Shirts legt die Hände im Kreis zusammen als Symbol für Teamzusammenhalt

5 Practical Methods for Conducting a Needs Assessment

Method 1: Activate the team perspective

Survey your employees anonymously or openly. Organize short team workshops or individual conversations to collect examples of challenges and burdens in their everyday work.

Practical tip

Don’t ask your team for ideas about AI. Instead, ask exclusively about specific problems they encounter in their everyday work. Then sort and prioritize the topics identified according to urgency and relevance.

Method 2: Observe processes objectively

Have selected workflows in day-to-day care observed step by step. Ideally, use someone from outside the respective area of expertise to gain an objective perspective.

Document the current processes and analyze where recurring delays or duplicate work occur, where information gets lost, or where reducing workloads would have the greatest impact.

Method 3: Involve residents and relatives

Also take the needs of residents and their relatives into account, for example through:

  • Written surveys (questionnaires, surveys)
  • Short conversations or structured feedback sessions
  • Analysis of existing feedback, e.g., from a suggestion or complaints box

Method 4: Make use of external networks

Use the expertise of provider organizations, professional associations, universities, or competence centers. Exchanging experiences with other care facilities can show you which solutions have already proven successful in similar situations.

Potential points of contact include:

  • Other care facilities: Do they have similar problems and pain points? Have they found AI-based or digital solutions? If so, which ones?
  • Provider organizations that support multiple facilities and have an overview of developments across organizations
  • Municipalities or state-level initiatives
    • An overview of the similarities and differences in decision-making structures in Germany and Denmark when identifying care needs can be found in Step 7 – Scaling. It shows which stakeholders are involved in decision-making and implementation processes in each country.
  • Professional associations that provide practical knowledge, recommendations for action, or networks
  • Professional societies that translate scientific findings into practice
  • Universities and research institutions, particularly those working in nursing/care, digitalization, or implementation science
  • Competence centers for digitalization or AI
  • Networks or model projects where experiences and best practices are shared

 

Method 5: Determine your level of maturity: The digital assessment tool

Before moving on to detailed planning, you should assess your facility’s existing conditions.

The scientifically developed KIP-RA assessment tool (from the ProKIP project, funded by the German Federal Ministry of Education and Research (BMBF)) supports you in this process.

It assesses your readiness across five dimensions, including process, technical, and social aspects, and recommends individually tailored implementation pathways.

What does “maturity level” mean?

The maturity level indicates how well an organization is prepared to introduce and use AI – from technical infrastructure and data protection issues to the team’s openness to change.

Organizational Readiness (ORIC): A tool for organization-specific needs assessment

An organization can be technically well equipped and still not be ready for AI. Conversely, an organization with average IT infrastructure can successfully introduce AI if everyone supports the project.

The scientific ORIC model (Organizational Readiness for Implementing Change) describes this readiness based on two pillars:

  • Shared commitment (Change Commitment): How strong is the motivation across the entire team to actively support and contribute to the change?
  • Confidence in their own capabilities (Change Efficacy): Does the team believe it has the necessary skills and resources to implement the change?

Practical tip

A high level of organizational readiness is more important than digitalization alone. Invest in motivation and trust at an early stage, before purchasing new software. Assess your organization’s readiness using the ORIC questionnaire (available in German, Danish or English; source).

Nahaufnahme zweier ineinander verschränkter Hände, eine ältere Person im Rollstuhl und eine Pflegekraft

Digital Maturity Across Countries: Germany and Denmark

In Germany and Denmark, the practical circumstances often differ:

Deutschland Dänemark

Infrastructure under development: The exchange of health data and the use of digital care documentation are undergoing an ongoing transformation process.

Focus on enablement: Success depends heavily on targeted training, clear processes, and local acceptance.

Strong digital foundation: Denmark has more advanced digital public services and interconnected health data.

Identical practical challenges: Despite a higher level of digitalization, Danish care facilities face the same challenges: interface issues, IT incompatibilities, and the need for coordination within teams.

Insight from the Care-AI project

The use of modern devices or digital documentation systems does not automatically mean a smooth AI implementation. Always assess your organization’s readiness individually and independently of the country’s overall level of digitalization.

Your Outcome After This Step

Once you have completed the needs assessment, you will have the following foundation in place:

  • Erfüllt:

    A prioritized list of the biggest challenges in your day-to-day care

  • Erfüllt:

    A clear understanding of the causes of process delays

  • Erfüllt:

    A well-founded basis for deciding where AI can meaningfully support your organization

What Happens Next

Your foundation is in place and the key areas for action have been identified? The next step is to gain clarity: In Step 2: The Importance of AI for Care, learn how to realistically assess the potential of AI, define suitable use cases, and avoid overwhelming your team.

Sources