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The more quickly we obtain, process, and visualize current information, the faster we can exchange ideas, and the more effective we are at improving outcomes.Ĭontinual improvement and value-add through data analytics can come in many forms. Real-time data analytics can generate credibility, which leads to trust and higher performing teams, another common Lean concept. FMI/Autodesk’s “Trust Matters” asserts that “technology can create trust, by improving transparency, enhancing communication, and providing evidence of success.” Data illustrating trends and patterns visually can effectively raise awareness and motivate change. The actual data that contributes to the message also brings credibility to the message. An example from the pull planning process would be pointing out to a trade: “you achieved 81% of your planned percent complete over the past 3 months”, or “you have made only 50% of your commitments over the past 3 months.” Delivered among a group of trades, a competitive spirit develops that helps motivate the team. The real-time, accurate information removes the obstacles that subjective statements sometimes pose and the disagreements that often disrupt progress. Wikipedia defines “analytics” as “the systemic computational analysis of data or statistics. It is used for the discovery, interpretation, and communication of meaningful patterns in data.” Data Analytics can (a) help us verify and understand the current state, (b) illustrate trends we may not currently be aware of, (c) provide intelligent insights, and (d) help us prioritize problems or root causes all for more informed and deliberate decision making.
The Deming Plan-Do-Check-Act cycle is the model used in Lean circles to talk about continual improvement. Expressed a different way, the cycle means: “plan, perform, monitor, and improve”. When we “check” after acting, or “monitor” after “performing,” we are using the past to predict and potentially modify events of the future. We are increasingly able to track project metrics. With the exponential growth of technology, use of more apps, and the advent of “big data”, data analytics is becoming more accessible and more important than ever.
Using Data Analytics to Drive Value and Improvementīy Betty Lynn Senes, Project Director, Sundt ConstructionĪs an industry, we need to improve. We need to provide better value for our clients. We do not hit schedule or budget targets as reliably as we think. A study from FMI and Autodesk, “Trust Matters: The High Cost of Low Trust” recently reported that “In the US alone, according to FMI, the cost of missed schedules is estimated to be $20 billion per year, excluding single-family construction projects.” Another study, “The Business Case for Lean”, from LCI/Dodge/McGraw Hill", indicates that 61% of “Typical Projects” complete behind schedule and 49% of “Typical Projects” complete over budget. Poor productivity, inefficient communication, or unplanned events or obstacles are just a few reasons for this. Embracing Lean philosophy and practices are shown to make a substantial difference, in comparison. The authors of “Business Case for Lean” article found that only 21% of projects with intense Lean practices completed behind schedule, and only 17% over budget.
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