Managing Risks and Controlling Projects: Crucial Role of Data in Single- and Multi-Project Environments

This article is inspired by the webinar featuring Epicflow co-founder Jan Willem Tromp and professor Mario Vanhoucke based on his latest book “The Illusion of Control: Project Data, Computer Algorithms and Human Intuition for Project Management and Control”. It isn’t a summary of the book and touches upon only limited aspects of risk management and project control that have been discussed at the webinar.

Any project goes hand in hand with uncertainty and risks, which should be properly handled to ensure the project’s success. In this article, we’re delving into the most essential aspects of efficient project management that can ensure successful and timely delivery, and also dwelling on the importance of project data for risk management in single-project and multi-project environments.

Pillars of Efficient Project Management and Successful Delivery

To make your projects delivered within their constraints and bring the desired outcomes, the following aspects are of crucial importance:

Clear objectives and scope
Basic project schedule (plan)
Intelligent resource management
Proper risk analysis
Effective communication
Stakeholder engagement
Earned value management (control)

Though projects can hardly be successfully delivered if one of these layers is ignored, we suggest focusing on the three essential elements: basic plan, risk analysis, and project control.

Risk Analysis: Essential Components

A risk is an event or circumstance with either a positive or negative effect on a project. To understand the impact of a risk-bearing event, a project manager should carry out a proper risk analysis to mitigate potential threats and avoid roadblocks to successful delivery. Any project management area isn’t immune to risks, whether it’s the planning and estimating stage, the process of project execution, or communication within a team, between groups, and with stakeholders.

It’s also important to understand that there are project management risks and industry-related risks. Speaking of the industry-related ones, risks can be unique or common across industries. For example, the aerospace and defense industry is associated with the following risks:

Volatility in the geopolitical and economic environment,
Competition in the domestic and international markets,
Exposure to cyber risks,
and others.

At the same time, cyber risks are peculiar not only to the defense industry, they’re common within medical, IT, construction, and other sectors.

So, what do you need for an efficient risk analysis?

First of all, you need data. Without project data, risk analysis and management are impossible, because any of the available risk management tools in project management won’t ever bring any positive outcomes without at least basic information about the projects.

The first thing you should do for effective risk analysis is to create a risk register, where you’ll keep track of all possible risks, prioritize them, track their impact, and list all possible responses. As a rule, a project manager creates this document at the planning stage and needs essential data about the project. A risk register is one of the components of a risk management plan and should be revised at the project execution stage.

Let’s briefly consider what you need to have to prepare for a proper risk analysis.

Project Plan

A project plan serves as one of the effective risk assessment tools as it presents the activities with dependencies, resources, the amount of work needed to be done, and timeframes.

Historical Information

Lessons learned are used to understand what risks occurred and when exactly, what things work well and what don’t, and help implement only the effective strategies of risk mitigation.

Real-Time Data

As risks may occur at any stage of a project lifecycle, access to real-time information is crucial. You cannot adequately respond to risks and deliver projects successfully if you don’t have a timely updated view of your environment.

Effective Communication

This involves communication between team members, project teams, and stakeholders. Effective interaction and information sharing are a cornerstone of efficient risk management.

Risk Management at Different Stages of Project Life Cycle

Risk management encompasses all stages of a project life cycle:

at the planning stage, a project manager should dwell upon all possible risks and think of the strategies to mitigate them;
at the execution stage, the most important thing is to control projects and make sure that the risks are properly identified and managed.

Let’s briefly consider some risk management tools in project management depending on the project stage.

Monte Carlo Simulation for Assessing Project Risks and Uncertainty

Monte Carlo simulation is a technique used to model and analyze the impact of uncertainty and risk on project outcomes. By running multiple simulations, project managers estimate the likelihood of achieving project objectives, such as meeting deadlines or staying within budget, under different conditions and variables.

Monte Carlo simulation offers several benefits in project management, including:

It provides a quantitative assessment of project risks and uncertainties, enabling project managers to make informed decisions and prioritize risk management efforts.
It allows project managers to explore different scenarios and their potential impact on project outcomes, helping identify optimal strategies and courses of action.
It helps identify the most influential variables and their impact on project performance, allowing project managers to focus resources on mitigating key risks.
It provides valuable insights for decision-making, such as setting realistic project targets, allocating resources effectively, and identifying opportunities for improvement.

To do the Monte Carlo simulation, a project manager needs the following types of data:

project schedule,
resource-related data,
cost estimates,
information about probable project risks,
historical data about previous projects, and
probability distributions.

Though this technique has numerous benefits, it also has some drawbacks. Here are some of them in terms of risk analysis and data management:

This method turns out to be complex and time-consuming, especially for projects with numerous variables and dependencies, i.e. multi-project environments. Developing accurate probability distributions and running multiple simulations may require significant computational resources and expertise.
This technique is based on data inputs, including historical data, probability distributions, and risk assessments. Gathering and analyzing the necessary data is challenging, especially for multi-project environments full of uncertainty.
Though it provides valuable insights into possible project outcomes, it doesn’t guarantee the accuracy of these predictions as they’re based on assumptions about uncertain variables, and actual project outcomes may differ from simulated results.

Risk-Based Project Planning with Reference Class Forecasting

Reference class forecasting is another efficient technique that has an advantage compared to others, for example, Monte Carlo simulations: it doesn’t require that much data, namely, only the data from past projects is needed.

Reference Class Forecasting (RCF) is used to improve the accuracy of project cost, duration, or other estimations by comparing them to similar completed projects. The fundamental idea behind RCF is to base future project forecasts on historical data from past projects that are similar in nature, scope, and complexity.

Its essence is collecting data about the projects with the further division into classes based on some characteristics, e.g., size, client, industry, country, etc. When a new project comes in, a project manager puts it into one of the existing classes and analyzes based on the conclusions made for this class of projects. At that, a project manager uses a simple statistical distribution based on Excel. For instance, if there was a cost overrun of 20% for an A-class project then estimations for the new project of this class should be increased by 20%.

RCF helps to assess the level of uncertainty and risk associated with the project forecasts. By comparing the forecasted outcomes with the actual results of similar projects, project managers can identify potential risks and develop mitigation strategies.

On the other hand, though this technique doesn’t require real-time data, it demands a lot of information about past projects. The fewer project types you have, the less efficient this technique appears for you. Besides, suppose you deal with multi-project environments, where dozens of different projects are involved. In that case, the uncertainty and risk levels are much higher, and basing risk analysis on this technique may become ineffective and inaccurate.

Controlling Projects: Most Popular Techniques

Earned Value Management

Earned value management is one of the effective techniques of project control. In turn, an earned value analysis (EVA) is a useful tool for project managers to measure the real progress of project tasks and projects in general. It assists in estimating completed work and forecasting the project’s eventual outcome by comparing the performed scope of work with the planned tasks. The results of the earned value analysis are utilized during the process of Earned Value Management (EVM), which scrutinizes discrepancies, patterns, and future projections derived from the earned value analysis findings.

EVA encompasses three key indicators:

Planned Value: This metric outlines the expected amount of work scheduled to be completed by a specific stage of the project timeline. When calculated before project commencement, it serves as a benchmark.
Earned Value: Unlike the planned value, earned value signifies the actual progress made, reflecting the value attained through the resources expended.
Actual Cost: As its name suggests, actual cost denotes the total expenditure incurred up to the present moment.

Efficiency Control

Efficiency control involves systematic monitoring, evaluation, and improvement of project processes and activities to optimize resource utilization, minimize waste, and maximize productivity. It focuses on ensuring that project tasks are performed as effectively as possible to achieve project objectives within the defined constraints.

Let’s consider an example to understand the role of efficiency control. Let’s say you get a signal from an EVM system about a delay and then you have to dive in as a project manager into details to find out the cause. Control efficiency is a tool that can help you find and understand the reason for the delay.

But what if you get reports about delays every week or so? Then you’re going to spend most of your time trying to find the problems. But not every signal of a delay is a real problem.

Implementing efficiency control will let you assess these warning signals and spend less time and effort figuring out whether this delay is going to affect projects or not.

So, the challenge here is to understand which warning signals are critical, which ones can be ignored, what preventative actions should be taken, and when exactly.

Here’s where risk analysis comes into play again. Doing a risk analysis upfront ensures proper efficiency control.

Risk analysis gives you the answers to the questions above: if you see based on the risk analysis that a delay is going to happen, you measure its potential impact on the project environment, and if the analysis tells you that the impact on your project won’t have any negative consequences, you just ignore such delay signals if they happen in reality. But is it as easy in practice as it is in theory, especially when a company runs multiple projects with a shared resource pool? Let’s try to figure it out by comparing single-project and multi-project environments.

Specifics of Risk Analysis for Single Projects and Multi-Project Environments

Let’s start by highlighting the main peculiarities of complex multi-project environments.

Resource constraints: as projects share the resources, if a critical resource falls ill, the progress of all projects gets jeopardized.
Prioritization challenges: with multiple projects competing for resources, project managers face challenges of prioritizing projects and allocating resources effectively. Balancing conflicting priorities and managing stakeholder expectations become essential to achieving overall organizational goals.
Increased uncertainty and risk levels: the more data and dependencies, the more stakeholders involved, the more risks the projects face.
Interdependencies: in complex multi-project environments, the success or failure of one project can significantly impact others.
Diverse stakeholder groups: managing stakeholder engagement and communication becomes more challenging, requiring tailored approaches to address the needs of different stakeholders.
Information overload: with multiple projects running concurrently, project managers and stakeholders may face information overload, making it challenging to prioritize and make informed decisions.

Now that we know about the specifics of multi-project environments, let’s dive into the challenges of managing them.

The necessity to set the right milestones

In a multi-project environment, you cannot specify and take into account all the details in the plan as you do for a single project plan. In complex multi-project environments, milestones play a crucial role as they serve some crucial purposes:

They help track progress by providing clear points of reference to examine progress across multiple projects.
Milestones facilitate effective communication among project teams, stakeholders, and management by providing common reference points for discussing progress, identifying challenges, and coordinating efforts.
They help in managing resources efficiently by providing insights into resource allocation and utilization across multiple projects. This ensures that resources are allocated appropriately to meet milestone deadlines and project priorities.
Milestones provide project managers and decision-makers with valuable information for making informed decisions. They serve as checkpoints for evaluating project performance, making adjustments to project plans, and allocating resources effectively.
And the most important thing in terms of our discussion is the role of milestones in risk management. They enable early identification of potential risks and issues across multiple projects. By regularly reviewing milestone progress, project managers can proactively address challenges and mitigate risks before they escalate.

This is why it’s critically important to set the right milestones to make them play the right role in risk management. What we’re talking about now is time buffers. Let’s dive into this topic in the subsection below.

Managing time buffers

To be prepared for uncertainty and Murphy’s strike at any time, and therefore, avoid delays, use time buffers. A time buffer is a certain amount of time, usually 50% of the extra time taken from every task estimate, that is added to every task of the project. But this approach is outdated and cannot bring positive results, because it makes projects vulnerable to student syndrome and Parkinson’s law, and makes project schedules bigger than they can be.

We at Epicflow have a different approach to buffer management and have our reasons for that. Instead of hiding buffers in tasks, we take the minimum time based on the effort estimation and add a buffer to the end of critical milestones or the very end of the project. Being guided by the rule “Leave the projects in a better shape than it was before you started your task”, resources save the buffer and complete their tasks as soon as possible, even though we don’t use task deadlines in Epicflow. As a result, a time buffer is always available for unexpected circumstances, which makes projects protected from delays.

Swimming in the ocean of data

Information about the project itself, about the tasks and dependencies, about resources and their competencies… The list goes on. And what if there are not just 2 or 3, but 10+ or even 100 projects in the pipeline? Then project data management becomes not just challenging, but impossible for a project manager, even though they use Excel or a traditional single project management tool.

Another challenge that appears because of an enormous amount of data is the difficulty of communication between the teams, their members, and stakeholders.

Project teams need risk analysis project management software that could help handle all this information: organize, analyze it, provide insights that a project manager could further use in their work, and of course, ensure proper communication.

How Modern Technology Can Help Manage Risks and Control Projects: Innovative Capabilities Through the Example of Epicflow

Epicflow is innovative software developed specifically for managing multiple projects with the shared resource pool and serves as a perfect project risk management tool. Let’s overview its main functionality to understand how exactly it can make the process of managing multiple project data easier and ensure project success in terms of risk analysis.

Giving insight into historical data

Epicflow provides historical data about the demand, availability, and output of your resources with graphs, which are easy to interpret. Thus, the Historical Load graph shows you how efficient your teams were during a certain period in the past. Based on the analysis, you can make conclusions and increase resource productivity in the future.

Providing real-time data

Epicflow has numerous instruments that keep you up-to-date with real-time information about your available resources, the amount of work they’re delivering, the state of your time and budget buffers, giving you a perspective of possible risks.

Predicting resource-related risks

Epicflow’s predictive analytics mechanisms let you know about possible bottlenecks providing you with an opportunity to develop a proper risk mitigation plan, and further test its efficiency with an AI-powered project risk management tool What-if analysis.

Making project scenarios

With Epicflow’s AI-driven features, you can not only predict resource-related risks but also test your decisions in a simulated environment without any risks to your real projects. Implement any changes and immediately see their future impact on your projects while working with this project risk management tool. Test as many scenarios as you need and choose the ones that bring the desired results.

Ensuring maximum flexibility for easy adaptation

If anything happens that may affect one of your projects, Epicflow recalculates priorities immediately. By eliminating strict project schedules, Epicflow lets its users be more relaxed and protected: they don’t have to rebuild the plan, and task priorities between multiple projects are computed automatically within seconds.

Delivering virtual assistance

If a bottleneck is going to occur, you’ll be the first one to know about it. Epicflow’s virtual assistant Epica is an innovative project risk management tool that notifies users about possible threats and provides insights into the ways to address the arising challenges.

These are not all the features of Epicflow. Book a call with our experts to learn how combining data-driven project management and innovative multi-project resource management software will let you reach your business goals with less stress and time.

References

Mario Vanhoucke (2023). The Illusion of Control: Project Data, Computer Algorithms and Human Intuition for Project Management and Control. Springer.

Mario Vanhoucke (2018). The Data-Driven Project Manager: A Statistical Battle Against Project Obstacles. Apress.