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Expert Artikelen OPC
schedule 18 December 2024
person Paul Bartels

From OPC Dashboarding to in-depth insights with Power BI and API integration

Create an overview of your project with dashboards and improve communication to stakeholders and management. Oracle Primavera Cloud (OPC) offers its own dashboard module for this purpose, which allows you to create visual representations of schedules, risks and costs. Despite this, the dashboard functionality of OPC remains limited when you really need in-depth insights.

Examples of OPC Dashboard functionality

At BAEKEN, we solve this by accessing the data from OPC via an API and further visualizing it in Power BI. In this way, we combine the power of OPC with the flexibility and analysis capabilities of Power BI, leading to smarter insights and better decisions.

The limitations of OPC dashboarding

OPC’s dashboard module provides a good foundation, such as standard charts and visualizations of project progress, trends, and tasks. OPC also makes it easy to share dashboards with colleagues and team members. Nevertheless, the system has its shortcomings:

  • Limited customizability and chart options;
  • No possibility to combine data with other data sources;
  • Less suitable for in-depth analysis and custom visualizations.

As a result, with OPC dashboarding, you are often stuck with superficial insights. For organizations that want more, accessing OPC data via an APIsouth is a solution.

From OPC data to flexible dashboards with Power BI

At BAEKEN, we use OPC ‘s API to make all available project data instantly and fully accessible. Through this link to Power BI, we bring data together and create in-depth, interactive dashboards that fit the needs of your project, program, or portfolio.

What makes our approach unique?

  1. Customized visualizations: KPIs, risk monitoring, resource utilization, and performance indicators are presented bespoke to your organization.
  2. Integration with other data sources: Combine OPC data with financial information, HR data, and operational reports for cross-functional analysis.
  3. Insight into risks and opportunities: Interactive dashboards show in real-time which tasks, risks, or milestones need attention.
  4. Easy communication: Clear, visual dashboards increase stakeholder support and make complex analyses easy to understand.

Looking ahead: tailored insight for the entire organization

By integrating OPC data into Power BI, you optimize your project management in a way that matches modern expectations of data-driven decision making. API-driven dashboards not only offer more flexibility, but also provide a broader perspective on project performance, budget monitoring, and resource management. Imagine: one-click access to project performance and the ability to make proactive adjustments at the project level.

Ready to take your Project Control to the next level?

At BAEKEN we are experts in accessing OPC data via API and translating complex project information into clear, visual dashboards in Power BI. We make sure your data truly works for you to help you better manage time, cost, and quality.

Contact us and discover how BAEKEN transforms your OPC dashboarding into valuable insights that let your projects, programs, and portfolios excel.

Examples BAEKEN Power BI – OPC Dashboard

 

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Expert Artikelen OPC
schedule 18 December 2024
person Paul Bartels

From OPC Dashboarding to in-depth insights with Power BI and API integration

Introduction

In lean planning, the troublesome but well-known planning method involves the physical โ€œsticker session.โ€ Team members gather around a board, post-its in hand, and stick on their tasks for the week. At the end of the week, the board is rearranged again because not all tasks have been completed. While this method can be effective, there are hefty drawbacks: lack of overview and no direct link to the overall project schedule.south In this article, I’ll tell you more about how Oracle Primavera Cloud (OPC) Task can provide a solution to this.

Make the leap to digitiation

Imagine being able to turn that chaos of paper and post-its into a smooth digital process. OPC offers the perfect solution with the Task Module. No more manually shifting post-its or miscommunicating on tasks. Everything is automatically linked to the relevant activities in the planning. This way, you keep an overview, make sure your team is always in sync and your planners experience less stress processing the lean planning.

Why the OPC Task Module?

  1. From stickers to clever integration
    With the OPC Task Module, the well-known โ€œsticker sessionโ€ has been digitized and improved. Tasks are directly linked to planning activities, so that shifts are immediately visible to the planner and they can quickly intervene to prevent delays. In this way, there is greater insight into ongoing activities within the project at all levels.ย ย ย 
  2. Constant real-time overview even on your phone
    No more manual shuffling on a physical board; with OPC, the team gets an up-to-date overview of all tasks and their status that they can even view on their phone through the OPC app.north_east This creates more insight and support within the team, since everyone can always see the current schedule of tasks. Delays are reported automatically, saving you time and solving problems faster.ย 
  3. Efficient collaboration and direct communication
    As with physical stickers, each team member or company gets their own colour in OPC. Tasks can be immediately ticked off when they are completed and those responsible for the next task are immediately notified via integrated handovers, so they can get straight to work on their task. This makes the entire process streamlined and clear.

Transform your project controls with OPC and BAEKEN

With OPC Task, you get a solution that not only meets the modern requirements of project management. It also provides a powerful tool to strengthen collaborations and make progress tangible. BAEKEN is ready to seamlessly integrate this innovative tool into your organization and support you and your team on your way to greater insight and success in planning and execution.ย 

Ready to take the next step?

Contact us for a complimentary discussion on how BAEKEN can help you implement the OPC Task Module. Together we will discover the possibilities to take your project management to the next level. Step away from the physical stickers and embrace the future of lean project planning with Oracle Primavera Cloud and BAEKEN!

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Expert Artikelen OPC
schedule 18 December 2024
person Paul Bartels

From OPC Dashboarding to in-depth insights with Power BI and API integration

Introduction

In the past, the Oracle Primavera Cloud (OPC) risk module was found to deviate significantly from Oracle Primavera Risk Analysis (OPRA), the long-established and reliable risk analysis software. The P50 and P80 data in OPC then differed by 30+ working days from the data generated by OPRA. Now we have conducted a risk analysis comparison between OPC and OPRA for a project again, and we report this analysis in detail here.

Method

The risk analyses were performed on all activities with 5000 iterations, without convergence and with the same random seed (1). The example project on which the analyses were performed contained more than 1000 activities and 125 risks, all of which were included. There were initially no uncertainties applied to this project, and subsequently an analysis with uncertainties was performed on all activities. These uncertainties had a minimum of 90%, most likely of 100% and maximum of 130%. The project analyzed spans a period of 5+ years. A risk analysis on costs was also done; this looked at what the effect of linking costs to different risks was. These costs were uniformly distributed with a minimum of 600k and maximum of 1.2 million. The project had three hard constraints regarding start times of three activities. Analyses were performed with and without these constraints. The response context was pre-response because active mitigation had not yet been performed on the project. Finish dates, P50 and P80 values, and deterministic probability were considered.

Results

The first comparison of OPC and OPRA shows that for the finish date of the tested project, the P50 and P80 values differed from each other by only 2-3 working days on a P buffer of 180 working days (i.e., the difference between P0 and P50). The deterministic probability was 5% for both OPRA and OPC, indicating that OPC is now reliable. The frequency of finish dates was similar for OPC and OPRA (Figure 1). The only difference was in the maximum date, which differed by 30 working days between OPC and OPRA on a P buffer of 492 working days, with OPRA scheduling the date later. However, this maximum date is an outlier in the 5000 iterations of the analysis, and is almost never reported in projects.

Figure 1. Comparison of the frequency of finish dates of the tested project over 5000 iterations containing P50 and P80 values.

In addition to the finish date of the overall project, we also looked at how the finish dates of intermediate milestones differed in the risk analyses of the two programs. For intermediate milestone 1, the P50 and P80 finish dates differed only 1-2 working days on a P buffer of 112 working days between OPRA and OPC, but for intermediate milestone 2, the P80 milestone had 8 working days of deviation on a P buffer of 152 working days and the P50 was the same for both analyses. The deterministic probability for one milestone was 5% according to the OPRA analysis and 5.9% for OPC, while at the other it was 22% for OPRA and 28.6% for OPC. The frequency graphs of both intermediate milestones show the same trend, as for the finish date of the overall schedule (Figure 2). For both milestones, there was a deviation between OPRA and OPC at the maximum finish date of 30+ working days (32 and 36 respectively on P buffers of 450 and 405 working days).

Figure 2. Comparison of the frequency of finish dates for two intermediate milestones of the tested project over 5000 iterations containing P50 and P80 values.

After some adjustments to the risks that followed from a progress update to the schedule, the risk analysis was run again, now with hard constraints on three activities so that these activities would always start on the constraint date. The P50 and P80 finish dates were the same for the OPC and OPRA analysis. The mean finish date also had a deviation of only 1 day out of a difference of 132 working days between mean and P0. There was a difference in deterministic probability though: 7% according to OPRA and 9.1% according to OPC. The maximum finish date had a large difference of 86 working days on a P buffer of 480 working days. The frequency graph again shows an equal trend between OPC and OPRA, but with OPC you see more hits on the deterministic finish date which explains the difference in deterministic probability (Figure 3).

The same analysis was also conducted without the constraints; for the P80 and mean finish dates, the difference between the OPC and OPRA analyses was still only 2-3 working days on 229 working days of P buffer. However, the P50 values had a difference of 27 working days on a P buffer of 174 working days. The frequency graphs were comparable, and this shows that even a very small frequency difference could cause the P50 finish date to differ so much between the two programs (Figure 3). Remarkably however, the deterministic probability of the finish date was almost equal between the OPC and OPRA analysis (5% and 5.4% for OPRA and OPC, respectively).

Figure 3. Comparison of the frequency for the finish dates of the overall schedule after being updated with and without constraints on 3 activities of the tested project over 5000 iterations containing P50 and P80 values.

Uncertainties

In order to consider also the influence of uncertainties, we conducted an analysis where an uncertainty of minimum 90%, most likely 100%, and maximum 130% was put on all 1000+ activities in addition to their normal risks. While this is an extreme example, it is the best way to compare how the OPC risk module responds compared to OPRA. The difference between OPC and OPRA in P50 and P80 values for the finish date was about 10 working days on a P buffer of 224 working days. This was somewhat larger than in the earlier examples, but still within the ranges that it is acceptable. In this comparison, the minimum finish date also differed by about 10 working days between the OPC and OPRA analyses. (This minimum finish date in all previous analyses was always the same in both comparisons because risks could only give run-out but uncertainties could also give run-in.) The deterministic probability was very low, as expected with so many uncertainties, where OPRA only reported <1%, while OPC was able to calculate a more accurate number (0.02%).

Risks with costs

We linked 8 risks, each related to one activity, to costs; this resulted in a deterministic probability (note: deterministic value is not a cost value) of 41% with the risk analysis in OPRA and 39.1% for OPC. The P50 values which were 7.14 โˆ™ 105 and 7.41 โˆ™ 105 for OPRA and OPC respectively, also differed from each other by only a few percentage points (3.6%). The P80 values were even closer together with 1.07 โˆ™ 106 for OPRA and 1.08 โˆ™ 106 for OPC. The entire distribution of total costs is nearly identical in the OPC and OPRA analyses (Figure 4).

We also discovered through these analyses that the cost is linked to the risk in OPC, but in OPRA to the activity within the risk. Therefore, if the risk occurs then there is a one-time cost associated with it in OPC. If the risk occurs and there are 5 other activities attached to this activity, then in OPRA there will be 5 costs. This means that for risks with multiple activities attached, it is good to realize that OPC and OPRA calculate differently.

Figure 4. Comparison of the total cost of the tested project over 5000 iterations containing P50 and P80 values. Eight risks with costs were used for this analysis.

Tornado graphs

In addition to standard analysis on finish dates and determining P-values, risk analysis is often used to look at which activities and/or risks now have the most impact on the schedule. In OPRA, this involves looking at so-called tornado charts. An example is duration sensitivity, which means how likely the duration of an activity could affect the overall finish date of the project (Figure 5). Also relevant here is criticality index, which represents what percent of iterations an activity is on the project’s critical path.

In OPC, this feature is called mean impact and shows how many days on average an activity and/or risk causes the project to lag. Virtually the same activities appear in the top 10 mean impact (OPC) and duration sensitivity (OPRA) analyses (Figure 5). The only activity that does not appear in the mean impact is activity 3; this activity has a constraint applied to it from the schedule, which may explain as to why OPC does not show it in the mean impact analysis.

These tornado graphs show that OPC does a good job of estimating the mean impact of activities; the program just has a different way of showing the impact of activities and/or risks compared to OPRA.

Figure 5. Tornado graphs of risk analysis of the overall schedule after update with constraints which show duration sensitivity from OPRA and mean impact from OPC.

Conclusion and discussionOPC to become the new standard for risk analysis, but when to use OPRA?

The OPC risk analysis module is now reliable enough to replace OPRA as the standard for risk analysis, even for large-scale and complex projects. This module is more user-friendly than the OPRA software and planning is already integrated into OPC so there is no longer a need to export the schedule separately to perform a risk analysis. In addition, OPC has already integrated weather risks into its risk analysis module and the platform will continue to evolve by adding more risk analysis functionalities.

One of the other main advantages of OPC over OPRA is the new โ€œrisk removal impactโ€ functionality. In OPRA, this process must be performed manually, which is time-consuming. With OPC, however, this feature can accurately measure the impact of individual risks on the schedule compared to other risks within the project.

Nevertheless, this does not mean that OPRA can be shelved for good. In fact, the software still offers advanced risk analysis functionalities that OPC currently cannot (yet) perform. The two most important of these are probability branching and criticality index.

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Expert Artikelen OPC
schedule 18 December 2024
person Paul Bartels

From OPC Dashboarding to in-depth insights with Power BI and API integration

Oracle Primavera Cloud (OPC) brings risk analysis and project planning together in one powerful platform. Previous analyses showed that the risk module in OPC was not yet reliable enough compared to well-known solutions such as the thorough Oracle Primavera Risk Analysis (OPRA) program. In this article, I explain why OPC Risk is now BAEKEN-approved.

Why choose OPC Risk?

  • Simple and direct
    With OPC, you perform risk management and planning within one platform, without exporting or complex steps. The integrated scoring matrix for qualitative risks can also be standardized across the organization. This means that risk analysis and management can be seamlessly integrated and compared across multiple projects. Risk analyses can also be displayed via dashboards for better communication to different stakeholders. This all-in-one approach saves time, keeps projects organized, and prevents errors.

  • Advanced features such as Risk Removal Impact
    OPC Risk offers the new feature โ€œRisk Removal Impact,โ€ which allows you to directly analyze the impact of individual risks; the net effect of each risk on your P-value is immediately apparent. In OPRA, this analysis had to be done manually by removing one risk at a time and redoing the risk analysis. This tool gives you more control and insight, which is essential in large projects.

  • Continuous innovation
    OPC continues to evolve and regularly adds new features, such as weather risks. Although OPRA still has unique advanced options, like probability branching and criticality index, OPC continues to better suit advanced risk analysis needs.

OPC Risk vs. OPRA

In the past, OPC Risk showed large deviations from expected values, thus it was not reliable enough. Recently, we retested OPC Risk and it now appears that the results are sufficiently reliable such that we have confidence in it.

During this recent test, I compared OPC Risk with OPRA. Both the P values at the finish date and intermediate milestones were analyzed. Furthermore, I examined the impact of uncertainties and constraints on planning, as well as the effects of tasks and risks via tornado graphs. Finally, I mapped the impact of risks on project costs. This analysis showed that the P-values of the finish date in OPC are now as expected instead of deviations of 30+ days, as was previously the case relative to OPRA. For the full analysis of all aspects examined in this study, read here.

Thanks to these improvements, OPC Risk is now reliable enough and therefore BAEKEN-approved for use in all your risk analyses, even on large and complex projects. OPC Risk’s ease of use and seamless integration with other OPC modules, covering all facets of Project Control, Project Management, and Portfolio Management, make OPC Risk the new standard for risk analysis.

BAEKEN: Your partner in reliable risk management

BAEKEN helps you fully leverage OPC as part of your project strategy. We are committed to a data-driven and sustainable project approach and support teams in successfully implementing OPC aligned with your goals.

With a focus on collaboration, innovation, and control over risk, BAEKEN provides not only technology, but also the expertise to take your projects to the next level. Are you ready to step up to efficient risk management?

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