How can historical data improve project estimation?

Historical data plays vital role incase of estimation as it provide details and items which one may overlook while doing estimation works. Further, it can also provide the accuracy of cost estimation by comparing the cost w.r.t to units e.g. Per km pipe length cost of a past project compared with the current per Km cost (after including economic factors) of similar pipe will provide an accuracy of the current estimate.

Historical data is essential, especially for project management, but also other areas of IT. I keep a list of Current IT Projects that my team updates. Part of that update is estimating the hours each resource expects to put into a project and then tracking at a high level how many hours they actually put in. This way we have a yearly baseline of how close we are tracking to our estimates. If an estimate is too far off we can examine it in further detail to see what might have happened. It also allows us to better judge new projects that are similar to older projects. All of this is super important to ensuring projects are on time and on budget.

Historical data is great information for project estimation. This historical data saves lots of time, money, and energy during research work. We need to collect these historical data from reliable tools and sources. We should also check whether this data help in the goal of the project.

Identify common risks and challenges: By analyzing historical data, project managers can gain insights into how past projects have been performed in terms of cost, schedule, and scope. This information can then be used to develop more realistic estimates for future projects. Identify common risks and challenges Benchmark performance against industry standards

Historical Data is simply Real-World Evidence, RWE, quantified experience that can be used to determine project timelines, budgets, warning thresholds and forecast success outcomes. Historical Data can also provide learnings of how not do do things next time!

Historical data provides a benchmark or starting point for estimating costs. By looking at what similar projects have cost in the past, you can get a sense of what your project might cost. This can be particularly useful when budgeting for a project that is similar in scope and complexity to previous projects. Once you have a reference point, you can adjust your estimates based on the specific scope and complexity of your project. If your project is more complex or has a larger scope than previous projects, you might need to increase your budget accordingly.

Historical data would be helpful in planning, estimations for the current and future. We can utilize the historical data by any project team or a project team leader for the purposes of gathering as much information about projects, activities, or events that had taken place in previous time periods. We can get adequate insight and background to the team when making decisions that will ultimately affect the project.

Historical data can significantly enhance project estimation by providing valuable insights from past projects. By analyzing the duration, costs, and outcomes of previous similar projects, you can identify trends and patterns. This historical context helps in creating more accurate estimates, reducing the likelihood of underestimating or overestimating resources, timelines, and budgets. It also aids in risk assessment by highlighting common challenges and how they were addressed in the past. Additionally, historical data enables continuous improvement as you can refine estimation models based on actual performance, leading to better decision-making and more successful project outcomes.

Collecting Historical data is not simple activity, where we can spend many hours to analysis with different teams who worked or collected on it previously and so on. Finding out the right data including date, time, location of the data for project needs and store it in internal repositories for future needs. Taking experts/SMEs decision while using it on any current development would be helpful when you are gathering the historical data.

Traditional Project Planning is great for this. But I tend to supplement that as well. I have all of the department projects roll up into a Current IT Project dashboard where I can keep track of estimated hours vs actual hours used by resource. I use Monday.com for this but there are a ton of similar products on the market that can help. Eventually, I will have several year's worth of documented projects to pull from.

Historical Data for Projects Historical data is needed for projects where you want to understand or predict something based on past information. For example: Weather Forecasting: To predict the weather, meteorologists use past weather data. Stock Market Analysis: Investors analyze past stock prices to make predictions. Traffic Planning: To improve traffic flow, historical traffic data is essential. Health Research: Researchers study past health records to find trends and make decisions. Business Sales Forecasts: Companies use past sales data to predict future sales.

Though the historical data is valuable for understanding the past and making informed decisions in various fields. Historical data can be reflecting the perspectives and priorities of the time. Historical data can lead to gaps in our understanding of historical events and trends. We have to check the data quality on the historical data. Historical data less comparable to current data where we are trying to analyze historical trends/patterns.

Although the outlined limitations may apply to some activities of the project scope, requiring estimation from scratch, other activities, whether main or auxiliary, may still not be subject to same limitations and may benefit from existing historical data. Hence, since it is very likely for a company that often / concurrently executes projects to have repeating activities, especially auxiliary, their estimates can be supported with historical data. Thus, in my understanding it is not a case of "either suitable or not", but "have solid procedures to assess and validate historical data applicability to expedite extimation at least partially".

While Historical data is important, decisions based on insights from historical data alone may not prove apt for certain projects. Let’s look at the same with an example: a manufacturing site attempting to improve its environmental monitoring plan, may obtain the optimum benefit from historical data (sampling points, duration, micro flora, identifying patterns, risk analysis, etc.) At the same time in today’s VUCA environment, upscaling the manufacturing cannot solely depend on historical data due to high fluctuations in raw material price, socioeconomic conditions, supply chain disruptions, resource availability, etc. use of historical data in planning phase & agility in execution phase must go hand in hand for the success of a Project.

Some tasks are predictable, some are absolutely unpredictable. Applying historical data estimates to manufacturing processes, client management, editing, or other reasonably repeatable tasks makes sense. Be careful to avoid applying historical data extrapolation to unpredictable tasks, like innovation or conflict resolution.

Define your data metrics before you start. What are these metrics for? Do they answer the question? Are they timeless, will they answer questions in the future? Who did What, Where, When, How long did it take them, and with Which Tools?

Improving historical data quality and usability involves several key steps: Firstly, validate sources for accuracy and reliability. Next, ensure data is well-organized, standardized, and easily accessible. Employ data cleaning techniques to rectify inaccuracies and inconsistencies. Implement metadata to describe the data context and enhance understanding. Utilize version control to track changes and updates. Regularly maintain and update the data to retain relevance. Employ robust security measures to safeguard sensitive information. Engage users for feedback and incorporate their insights for continuous improvement. By focusing on accuracy, organization, security, and user involvement, historical data quality and usability can be improved.

Remember when measuring success to quantify it. Success is not a single line that one crosses, but a sequence of events that generate data, that led to success. Equally when measuring failure. Identify the root cause and the sequence of events that generated data. The data may be suitable as warning threshholds for a suitable project.

Historical data is a valuable tool for improving the accuracy and reliability of project budgets. It provides a solid foundation for cost estimates, allows for adjustments based on project specifics, helps in planning for uncertainties, and supports ongoing budget management.

Historical data, rather than enhancing project estimation, can sometimes hinder accurate planning. Relying heavily on past project data can lead to a false sense of security, causing project managers to underestimate the unique challenges and complexities of new projects. This results in over-optimistic estimates, setting unrealistic expectations and potentially leading to missed deadlines and budget overruns. While historical data can provide useful insights, it's essential to approach each project with an open mind and consider its individual characteristics to ensure more accurate and tailored project estimation.

Historical data is not a magic bullet but should be used cautiously in the light of sound judgment, experience and the uniqueness of the new project(s).