How to Structure Project Data for AI-Ready Reporting

This is the one most PMOs miss. Current status tells you where you are. Historical snapshots tell you velocity, trend, and pattern which is what AI reporting actually needs to generate insight rather than just recite today's numbers. </p><div><br></div><p data-start="4092" data-end="4118" class="PDq2pG_selectionAnchorContainer">Today's status can answer:</p><ul><li data-end="4151" data-start="4120">Which projects are at risk?</li></ul><div><br></div><p data-start="4153" data-end="4182">Historical states can answer:</p><div data-end="4423" data-start="4184" style="font-weight: normal;"><ul><li><div><span>Which projects are deteriorating?</span></div></li><li><div>Which projects repeatedly recover after turning red?</div></li><li><div>How long do projects typically remain at risk before slipping?</div></li><li><div>Which conditions tend to appear before a project misses its target?</div></li></ul></div><img 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" class="e-rte-image e-imginline" width="auto" height="auto" style="min-width: 0px; min-height: 0px; max-width: 100%;max-width:100%;"><br></div><div><br></div><h3>7. Preserve the relationships between your data</h3><div><p data-start="3213" data-end="3484" class="PDq2pG_selectionAnchorContainer">A project isn't useful to AI as an isolated record. It needs to be connected to the things around it: the request that created it, strategic initiative it supports, people assigned to it, approved budget, actual costs, milestones, risks, decisions, and reporting periods.</p><p data-start="3486" data-end="3507">For example, knowing:</p><ul data-start="3509" data-end="3579">

<li data-start="3509" data-end="3543">

Project A = $800,000 actual cost

</li>

<li data-start="3544" data-end="3579">

Initiative X = strategic priority

</li>

</ul><p data-start="3581" data-end="3721">doesn't allow AI to answer whether Initiative X is over budget unless the relationship <strong data-start="3668" data-end="3696">Project A → Initiative X</strong> is explicitly preserved.</p></div><div><br></div><h2>What specific data do I need for common AI-ready project reports?</h2><p>The goal of AI-ready project data is not just to make your fields cleaner. It is to make sure you are capturing the specific data AI needs to answer the questions your leaders actually ask.</p><p>A good way to test your project data is to work backward from those questions. Start with the report or decision your executive team wants, then identify the data points required to answer it reliably.</p><div class="table-responsive">

  <table class="table e-rte-table">

    <thead>

      <tr>

        <th>Executive question</th>

        <th>Project data required</th>

      </tr>

    </thead>

    <tbody>

      <tr>

        <td>Are any strategic initiatives over budget?</td>

        <td>Project ID, strategic initiative, approved budget, actual cost, reporting period</td>

      </tr>

      <tr>

        <td>Do we have the capacity to take on two new projects next quarter?</td>

        <td>Resource, role or skill, availability, current assignments, percent allocation, assignment dates, future project demand</td>

      </tr>

      <tr>

        <td>Which projects are likely to miss their target dates?</td>

        <td>Baseline dates, current forecast dates, milestone history, task progress, dependencies, historical project status</td>

      </tr>

      <tr>

        <td>Which projects should we reconsider?</td>

        <td>Priority, strategic alignment, project health, cost, resource demand, expected outcomes or success criteria, decision history</td>

      </tr>

      <tr>

        <td>Where are we consistently underestimating work?</td>

        <td>Original estimate, planned effort, actual effort, task or project type, completion date</td>

      </tr>

      <tr>

        <td>Which portfolios are consuming more capacity than planned?</td>

        <td>Portfolio and project relationship, resource assignments, planned allocation, actual effort, resource capacity, reporting period</td>

      </tr>

    </tbody>

  </table>

</div><div><br></div><h2>What about structuring project data for a database?</h2><div style="text-align: start;"><p class="isSelectedEnd"><span>If your team is working in a PPM tool or building an internal project database rather than managing project data in spreadsheets, the same principles still apply. The difference is that the structure is often being defined behind the scenes through system configuration.</span></p><p class="isSelectedEnd"><span>The question shifts from, “Am I entering this data correctly?” to, “Was the system configured to capture this data correctly, and are people using it consistently?”</span></p><p class="isSelectedEnd"><span>A few things to check:</span></p><ul data-spread="false"><li><span>Are your field types correct? For example, is budget stored as a numeric or currency field rather than a text field?</span></li><li><span>Are picklists and dropdown values standardized, or can users override them with free text?</span></li><li><span>Are important project objects connected to one another? Can a project be reliably tied to its request, strategic initiative, resources, budget, approvals, and other related records?</span></li><li><span>Does your system preserve historical values or snapshots so you can see how status, forecasts, budgets, and other measures changed over time?</span></li><li><span>When data moves between systems, are the same projects, resources, departments, and other records connected using consistent identifiers?</span></li><li><span>Do you have a data dictionary that defines what each field means, which values are valid, where the data comes from, and which system is the source of truth?</span></li></ul><p><span>A well-configured system does more than store project information. It gives that information a consistent structure, preserves the relationships between it, and makes it easier for reporting tools and AI to interpret it reliably.</span></p><div><br></div><h3>Why is a connected project data backbone so important?</h3><div><br></div><div>When the project data backbone is connected, consistent, and structured, project reporting stops becoming a monthly <span>reconstruction project, and </span><span>AI can reliably analyze your project data instead of trying to interpret scattered fragments or guessing at inferences. </span></div><div><br></div><div>AI-ready project data isn't created by adding AI to the reporting process. It is created by building the project data backbone underneath it: capturing the right information, structuring it consistently, connecting related data, and preserving its history.</div><div><br></div><div>Once that backbone exists, dashboards become easier to trust, executive questions become easier to answer, and AI can analyze the data rather than trying to reconstruct what it means.</div><div><br></div><div><span>Score your PMO on data readiness, or explore how connected project data supports executive decisions.</span></div><div><br></div></div><div><br></div><section aria-label="Explore project data resources" style="padding: 32px 0;">

  <div style="display: flex; flex-wrap: wrap; gap: 24px; max-width: 1000px; margin: 0 auto;">

    <article style="box-sizing: border-box; flex: 1 1 320px; padding: 32px; background: #f7f9fc; border: 1px solid #dce4ed; border-radius: 8px; display: flex; flex-direction: column; text-align: left;">

      <p style="margin: 0 0 12px; color: #52657a; font-size: 12px; font-weight: 700; letter-spacing: 1.2px; text-transform: uppercase;">PMO assessment</p>

      <h3 style="margin: 0 0 16px; color: #12334f; font-size: 22px; font-weight: 600; line-height: 1.35;">Score your PMO on<br>data readiness</h3>

      <p style="margin: 0 0 28px; color: #37475a; font-size: 16px; line-height: 1.6; flex-grow: 1;">See how ready your project data is to support reporting, forecasting, executive decisions, and AI.</p>

      <a href="https://projectinsight.com/resources/project-data-maturity-quiz" style="display: block; padding-top: 18px; border-top: 1px solid #dce4ed; color: #1264a3; font-size: 16px; line-height: 1.5; font-weight: 600; text-decoration: underline; text-underline-offset: 4px;">Score your PMO →</a>

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    <article style="box-sizing: border-box; flex: 1 1 320px; padding: 32px; background: #f7f9fc; border: 1px solid #dce4ed; border-radius: 8px; display: flex; flex-direction: column; text-align: left;">

      <p style="margin: 0 0 12px; color: #52657a; font-size: 12px; font-weight: 700; letter-spacing: 1.2px; text-transform: uppercase;">Project Insight’s guide</p>

      <h3 style="margin: 0 0 16px; color: #12334f; font-size: 22px; font-weight: 600; line-height: 1.35;">Connecting your data for<br>executive decisions</h3>

      <p style="margin: 0 0 28px; color: #37475a; font-size: 16px; line-height: 1.6; flex-grow: 1;">Read the story of how connected project data gives leaders a complete picture for executive decisions.</p>

      <a href="https://50795418.fs1.hubspotusercontent-na2.net/hubfs/50795418/Project%20Insight%20Strategic%20PPM%20Software-1.pdf" style="display: block; padding-top: 18px; border-top: 1px solid #dce4ed; color: #1264a3; font-size: 16px; line-height: 1.5; font-weight: 600; text-decoration: underline; text-underline-offset: 4px;">Read the story of connected data →</a>

    </article>

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