Making the data work hard When looking at our own Decarbonomics TM offering, one of the key drivers has been how we can accurately benchmark an organization’s estate with very little building survey data and still deliver robust and highly precise outputs. The mission is to help clients understand when enough data is enough and to minimize upfront costs, shrink pre-delivery program durations and enable them to move to delivery as quickly and efficiently as pos - sible, without compromising long-term delivery performance. The more data you have or have access to (such as open-source bench - marks which are becoming increasingly available) the more powerful data-driven solutions will be. However, data alone is just the fuel. You still need the engine and, in this case, that engine is the intelligent analytics—algorithms, AI, and
machine learning—that we apply to the data for robust and accurate outputs that can be visualized and interrogated by a diverse mix of users, from technical delivery teams to finance leads. Ultimately, the true power of smart, data-driven solutions is how they combine the best human expertise, data and technology. No matter how many clever digital and data systems we apply to these problems, it’s people who must drive the system and guide the outputs. With the scale of the challenge ahead, we must deliver achievable and cost-effective net zero plans for today. A theoretical net zero future, based on wishful thinking around behavior changes and new technolo- gies isn’t going to help us reach our goal that’s only 28 short years away.
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