The importance of being data literate

As an industry, we are deep in the throes of a digital revolution, one that is happening slower than we might have hoped for. This gradual pace is not just a reflection of the inherent complexities in adopting new technologies, but also a stark reminder of the pressing need for enhanced data literacy within our ranks. The construction sector, known for its tangible outputs and physical landscapes, is now navigating an era where intangible data plays a pivotal role.

Data literacy is a measure of an individual’s ability to comprehend, create and communicate data effectively. Data itself is not a new concept, even in construction: we’ve been a data-heavy industry for years. Take a look at DIM sheets or PERT diagrams of the past and you’ll see data that is fairly similar to what we see today. The key difference is that there is so much more of it now. We produce more, share more and store more than we ever have. There is no need to curate the data if the cost of storage is essentially zero.

In light of this firehose of data, we need to ensure we can find ways to extract the value to create decisions that have positive impacts on our projects. This is where data literacy comes in.

One of the simplest yet most effective approaches to embrace data literacy is by understanding and implementing the ‘three Cs of data literacy’: curiosity, creativity, and critical thinking. Curiosity serves as the starting point: it motivates us to delve deeper into data, identify emerging patterns, and question any discrepancies we encounter. In the construction industry, this might involve a project manager investigating repetitive delays to discover underlying causes and potential solutions. For a business, fostering curiosity is essential for creating value, otherwise, we risk turning into mere cog-turners, adhering to routine simply because, in one way or another, the project will reach completion.

Next comes creativity, which is crucial in crafting innovative ways to interpret and analyse data. In construction, the general consensus is that each project is different, thus each will require creative problem-solving to maximise the potency of data.

Last, critical thinking is essential, acting as a safeguard against misunderstanding and leading to well-informed decisions. In practical terms, this is where we thoroughly assess the data and conclusions to make sure they are valid. It is easy to see a set of numbers fall out of a spreadsheet and label them as infallible, but we have to understand whether the calculations are robust and the inbound data was complete.

The overarching goal is that enhanced data literacy will pave the way for higher-quality decisions, leading to compounded benefits over time. A prime illustration of this principle in action is the ‘plan, do, check, act’ cycle of continuous improvement, used heavily in the manufacturing sector. This repetitive, four-step approach for ongoing improvement ensures you plan a change, implement it (do), review the results (check), and then use what you’ve learned to make further enhancements (act), repeating this cycle for continual progress.

By systematically applying this approach, we can gradually discover more efficient and effective ways to deliver projects. It involves making incremental adjustments to processes, informed by data insights, rather than attempting to leap directly to the final outcome.

This methodical progression contrasts sharply with the challenges faced in adopting offsite manufacturing. Offsite manufacturing’s struggle to gain traction may partly stem from its leapfrogging nature, bypassing the gradual evolution and refinement of processes.

By embracing a more incremental approach, grounded in data-driven insights, we might better navigate the complexities of project delivery and unearth innovative solutions that are both effective and sustainable.

One of the phrases you hear quite a lot while implementing digital change is ‘rubbish in, rubbish out’ (often substituting ‘rubbish’ for the speaker’s profanity of choice). The way it is delivered often implies that the incoming ‘rubbish’ is an inevitable fact, almost accepted as a foregone conclusion. Data literacy is the tool that corrects and refines this information for the benefit of downstream stakeholders.

Consider the example of spreadsheets: when used correctly, they are incredibly effective tools, yet improper use can create significant problems. Despite being major repositories of industry data, efforts to strictly control them often meet with creative workarounds. The solution lies not in punitive measures for non-conformance, but in encouraging better practices.

By educating people about the value of data, its purpose, and ways to extract maximum benefit, we can achieve far better outcomes. Especially when our aim is to make incremental, rather than large, generational improvements, the contribution of these individuals in refining processes becomes crucial.

How many Excel documents have you seen lately that use formal Tables, PowerQuery, Pivot Tables, Lambda functions, or named ranges? Instead, we often rely on fragile formulas, decades-old Visual Basic scripts and colour formatting in documents.

In the next articles in this series, I will take a look at how to enable a more data-literate workforce, and what outcomes you can expect as you improve the data literacy within your business.

Matthew Osment is a consultant in the construction industry. He recently founded Shift to deliver digital transformation in the sector in more innovative ways. By offering free, open-source tools for data management and creating free content and training, Shift hopes to empower construction professionals to start making incremental change in their businesses and apply the concept of continuous improvement to construction.

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