Project success and why quality management matters

[edit] Introduction

Poor decisions made using ‘bad data’ cost the construction industry £1.3 trillion globally in 2020, with bytes of data at the root, running up rework bills of £63million, according the Autodesk/FMI report 'Harnessing the Data Advantage in Construction'.

These numbers suggest greater emphasis is needed on collecting and surfacing accurate data with efficient data handling at all stages of the building project. Sector-specific quality management tools can weed out expensive errors. generate cost savings and increase data efficiency across the board for housebuilders, developers and other construction professionals.

[edit] What is the issue?

Bad data, as the Autodesk/FMI report spells out, is bleeding profits for construction companies, despite the industry converting to more digital methods to manage and understand it. A survey of 1,115 construction professionals,as part of the report highlights the need for change, as data obtained is either unclear or unusable. At worst, professionals are unclear about exactly what type of data needs to be obtained, and how it should be stored and managed. For building regulations like Part L, where digital data might be mandatory to ensure compliance, lacking or bad data could lead to an inevitable delay of project completion if costly and invasive reworks were required to obtain it.

The FMI report states:

• 82% of professionals are collecting more data from construction technology today than three years ago, but 39% say that less than half of that data is usable
• 40% of the average organisation’s data is bad – meaning inaccurate, incomplete, inconsistent or untimely information
• Professionals report problems with the whole process, from knowing what data to collect (51%) to understanding how to manage project data effectively (52%)

With such widespread problems, clarity must be a priority when dealing with project data.

• What is needed?
• When is it needed by?
• Who is collecting the data?
• Where does the data go and where is it stored?
• Why is this data being collected?
• And how can the data be easily shared with key stakeholders and collaborated on?

By answering these questions, those in the construction sector can make better decisions to build better, avoiding costly reworks and complying with mandatory regulations like Part L, and the Building Safety Act. By integrating the right solution, these questions can be answered, as a tool built for these demands will be pre-configured to prioritise and standardise structured data.

Which also means that mandatory requirements in regulations such as Part L will simply be another milestone in a project rather than an obstacle.

[edit] Comply with Quality Management

Part L, as an example, requires that SAP assessors have evidence and data presented promptly, so EPCs (Energy Performance Certificates) and the BREL Report (Building Regulation England Part L Report) can be released. The as-built BREL Report must be completed and presented to the SAP assessor prior to the EPC being produced. An on-site audit of building details and thermal elements will be required during construction and at completion for building regulations approval, including photographic evidence to confirm all new builds and refurbished dwellings are constructed correctly using materials and technology that ensure energy savings and meets building regulation standards.

A centralised platform that collates, standardises, stores and shares all documentation and data, would make Part L a simpler part of the building project process, as opposed to a major obstacle.

Even though construction professionals are collecting more data digitally than ever before, there are plenty that are using the wrong tools for the job. Ambiguous software and platforms that don’t standardise or structure data and don’t offer the required level of quality management mean that any data can slip through the net. Some projects are using a multitude of solutions that synchronise, rendering data and documentation unclear, in silos and even worse – incorrect.

• Massive delays can be a symptom of bad data quality management.
• Get the data seal of approval with the right Quality Management

A clear process, outlined from the beginning and with all stakeholders involved with data acquisition, is key to ensuring any data that is collected, is valuable and understandable.

Templates and guidelines that highlight common standardisations to ensure the right data is gathered, direct where the data should be stored and make the data transparent with a user-friendly experience, accessibility and labelling of data, would help teams align and increase efficiency. Is there a better way to focus your team’s efforts on productive activity, increase efficiency and work towards a swift and satisfactory conclusion, than with a platform where everyone has the data they need at all times and know what they need to do with it?

Erroneous and badly aligned data slow down progress and can make regulatory compliance – something your project depends on – a slog, rather than simply another well-signposted milestone in your process.

A Quality Management solution gives you and your team the templates, workflows and dashboards to capture, mark-up, trace and share all photographic evidence and present it for assessors. It avoids confusion on what data to collect and helps every stakeholder know what needs to be done at every stage. You’re missing photographic evidence for a plot or there is documentation missing? An intuitive and clear dashboard that tracks Part L evidence progress fits the bill and dispels any confusion.

--Zutec 09:59, 19 Dec 2022 (BST)

[edit] Related articles on Designing Buildings

• Brief.
• Communication and document control - the way to project success.
• Construction quality management guide.
• Design quality for buildings.
• Digital quality management in construction.
• Dynamic conditions for project success.
• Data.
• Information.
• Initial project brief.
• Initial success criteria.
• ISO 9001.
• Project brief.
• Project success criteria.
• Pareto analysis.
• Quality assurance.
• Quality control.
• Quality in construction projects.
• Quality management systems (QMS) - beyond the documentation.
• Quality manuals and quality plans.
• Selection criteria.
• Statement of need.
• Strategic brief.
• Success criteria.

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