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The barriers to creating great data strategies aren’t generally specific to the construction industry, but some of the considerations are – particularly as the world moves towards smart cities and sustainable construction.

It’s important to remember that the data journey doesn’t have to be completed in one go, so you shouldn’t feel obliged to do everything at once. The logistics, costs and resourcing involved in launching a data strategy can be overwhelming, and that’s even before setting a priority list for what the data strategy should address.

Implementing the plan in stages that specifically address the firm’s most pressing needs one by one is just as effective, and could be more effective, than taking a zero-to-100 approach.

Getting started with a data strategy

Establishing data ownership in terms of leadership and investment is crucial when it comes to staying competitive. Two of the most common data strategy and management hurdles are ones that can be easily overcome. They are: 

1. Involving all stakeholders, not just IT
   Most data initiatives are IT-lead, and so are less likely to achieve the necessary traction in the wider business. Getting stakeholder buy-in is essential, and having senior leadership communicate the importance of the data project and its expected outcomes underlines how integral to the business plan it is. Stakeholders in the construction industry will include all parties in the supply chain, contributing to the project design, build and delivery. Data ownership, capture and risk management are key considerations when building a process to interrogate the data.
2. Lack of consistent terminology and software
   A lack of common terminology and software across large businesses can make data gathering very difficult. The solution is training across teams and departments to get everyone speaking the same language. Using the same applications and methods for recording and analysing data company-wide makes data gathering and reporting much easier. Different teams will make different use of the same construction data, but at the very least the data sources and terminology should be something everyone in the firm has in common.

The good news is that addressing both of these also conveniently deals with another widespread problem – a lack of data sharing because of a reluctance to publicly own and rely on it. It’s common for senior leaders in the construction industry to mistrust their data because they don’t really know where it came from, and they don’t feel like they can confidently make assertions based on it. 

Managers may be comfortable with the methods used by their own team, but those methods may be different from those used by finance teams (for example). Different allocations or calculations result in divergence in the data sets, so standardising the way data is recorded is about far more than just good admin.

Is bridging the data gap worthwhile?

Many large, well-established firms will recognise that finding and organising their data is not a simple task. Information from on-site may be scribbled into notebooks, stored on phones, or hastily recorded on various spreadsheets. Salvaging this ‘bad’ data is possible, but it’s a judgment call as to whether its final value will justify the time and resource required to get it. Instead, it may be more sensible to look at reforming current data governance policies.

Spreadsheets and notebooks aren’t going away, but they’re not suitable for recording mission-critical information. Project managers who are on-site and logging their resource needs and the time taken on each stage of a build need to have a robust process for recording that data. This process needn’t be overly expensive or complicated; bespoke solutions are available to tackle a specific issue, as are power ups that can be added to existing applications to enable more efficient real-time reporting.

Getting hold of the data you want and need is incredibly important and requires investment in the hardware. Old apps are hard to get data out of, and upgrading is worth it because it’s a repeatable process. You don’t want to analyse the data in the same app that created and stored it, such as an enterprise resource planning (ERP) system.

Commercial advantages of good construction data management

Reporting is one area where good data management can make a world of difference, but there are other commercial and operational advantages.

For example, most firms have a multitude of suppliers and work with numerous contractors. Do they know how often certain suppliers deliver late? Or deliver the wrong product to the wrong place, or in the wrong quantities? How often does a labour contractor provide workers who don’t have the right skill level for the job, or workers with performance issues? Can the information from the risk log be overlayed with the project timelines to identify, for instance, whether the risk of non-supply was correctly identified?

Where there are marginal cost differences between suppliers of labour and materials, good data can illuminate why projects are being delayed and where unexpected expenses are coming from. There’ll always be someone in the business who has a ‘feeling’ that they know where the pain points are, but there are guaranteed to be surprises hidden in the data – ‘the unknown unknowns,’ to borrow a phrase.

Uncovering these issues requires good data literacy at all levels, including knowing how to accurately present it: Data can be very misleading if the story isn’t presented in the right way.

Fortunately, over time most of us will become more comfortable with technology and data. Project managers now have a reasonable expectation that they can see the status of all of their projects at the touch of a button. It’s these changing expectations of ways of working and outcomes that underpin how data strategies and management techniques will continue to evolve.