Using data-led tendering to win more work

Gone are the days of basing project tenders on guesswork alone. More and more contractors are using data analysis to inform their project estimates and add evidence to years of construction experience.

The way a tender is managed can have a dramatic impact on the delivery, cost and overall result of a project. In an increasingly competitive industry, success can hinge on the presentation of a well-thought-out and data-led tender.

Here’s how you should be using industry data to give your business the edge.

Use previous project information for estimates

Using data from similar projects can help you to create a more accurate estimation of project costs, requirements and outputs. Traditionally, Project and Construction Managers have used their personal experiences to inform these estimations but they are based on memory, not data. Having a verified source of truth ensures that these figures are correct.

For example, an existing Raildiary client used their project data to tender for a new framework. By using this method they realized that their actual outputs were lower than expected due to recurring risks that they had not accounted for. As a result, they adjusted their project schedule, resource requirements and provided a more detailed risk register based on actual events.

They still won the project because the client placed more trust in their tender based on real evidence. They now deliver the works on a much more sustainable and predictable basis for the business.

Identify trends in customer requirements

Data analysis can be used to identify recurring client requirements. Predicting this demand ahead of time means that you can tailor your tender to fit the priorities of the time. For example, Network Rail is currently championing issues such as innovation, environmental impact and engaging SMEs. Monitoring these trends gives you an advantage over those who may be relying on a more generic tender model.

Monitor the supply chain

Monitoring the supply chain to compare real-time pricing, availability and demand helps you get the best quality resource at the best possible price. Include accurate, up-to-date costing in your tender and engage with the supply chain to build an ecosystem of niche specialisms and reliable suppliers.

Compile unstructured data

Bring together unstructured data such as WhatsApp messages, email and media for a full picture of project requirements. Present your future client with examples of progress reports and before and after photos to build confidence in your offering.

These sources can also be used to identify certain trends within a project, such as environmental issues that continuously crop up or safety considerations to be taken into account.

Collating all of these data formats can be time-consuming, so consider adopting a single-source reporting platform like Sitediary.

Identify risks and address them head-on

Your bank of historic data could bring to light certain risks that you haven’t noticed or accounted for before. If a particular activity is repeatedly delayed by, say, insufficient resource, account for this within your tender and explain how you’ll combat it. This forward-planning shows your in-depth understanding of the nuances of the project and builds confidence in your ability to deliver the project on time.

Compare against industry average

Don’t just focus on internal information. Combining your project data with relevant external data assets gives you the opportunity to benchmark your performance against rival contractors, based on real figures.

For example, we recently published data sets comparing average outputs for a range of key OLE and Power and Distribution activities. By analyzing your own project data against these, you can identify whether your outputs are competitive or need further improvement.

In conclusion, data-led tendering is transforming the railway industry by providing a more efficient, cost-effective, and sustainable approach to procurement. The use of data analytics tools allows rail operators to gain valuable insights into their supply chain, enabling them to make more informed decisions about suppliers and contracts.

The implementation of a data-led tendering is not without challenges, however. One of the key challenges is the need for a cultural shift within the industry, which requires a greater focus on data literacy and the willingness to embrace new technologies. Additionally, there may be resistance from suppliers who are not familiar with data-driven procurement processes.

Despite these challenges, the benefits of data-led tendering are significant. By leveraging data, rail operators can create a more transparent and competitive procurement process that ultimately benefits both buyers and suppliers. In addition, data-led tendering can help to drive innovation by encouraging suppliers to develop more efficient and sustainable products and services..