By Kenny Ingram, Director of Engineering, Construction and Infrastructure, IFS

The move to a data-driven digital asset lifecycle is causing a huge disruption in the industry across all stages of an asset’s life.

Different digital technologies are starting to impact how construction projects are delivered and how assets are subsequently operated and maintained. These include BIM (Building Information Modelling), 4D and intelligent scheduling, 3D printing, drones, mobility, laser scanning, robotics and automation, virtual reality, the Internet of Things (IoT), cloud computing, big data and analytics.

These digital technologies will collect a vast amount of data, so the need to manage this data and drive intelligent actions and decisions is going to require smart solutions. Today, most companies involved in the asset lifecycle are struggling to manage the information they have now. Their business and IT solutions are usually not integrated and it is very common for users to manage these large projects on Microsoft Excel spreadsheets. This traditional approach will simply not work in the future, so change will be essential for most organisations if they are to survive in this new digital world.

Organisations that embrace these new technologies are likely to be winners in the future. It is likely that the shape of the industry will change dramatically over the next 10 years with many traditional players going out of business and new entrants taking the initiative.

“Digital transformation is not just a technology trend; it is at the centre of business strategies across all markets and segments,” says Jason Anderson in a recent IDC report. Enabled by the four technological pillars of social, mobile, cloud and big data/analytics, digital transformation represents an opportunity for companies to redefine their customers’ experience and achieve new levels of enterprise productivity.

Executives are being driven to implement big data/analytics strategies through pressure from clients, competitors and employees (i.e., internal stakeholders) that collectively drive greater demand for data capture, management and analytical software. Clients expect companies to have detailed granular information at their fingertips; the competitive landscape is driving innovation through new competition and faster time-to-innovation enabled through data-driven insight; we need to have the ability to collaborate with subcontractors and co-workers – and to leverage that collaboration for business decision-making.

Those solutions having the greatest impact in meeting these demands will be the ones providing real-time, accurate, actionable intelligence.

How big data and analytics are transforming asset lifecycle industries

For organisations involved in building, operating and maintaining assets, the benefits of big data have the potential to be profound. Digital technologies are not only transforming the industry, they’re also benefitting the companies which embrace change.

Some digital transformation technologies have a greater focus depending on whether you are involved in constructing the asset or maintaining and operating it. For example, BIM has had a greater impact on the construction phase and big data, IoT and analytics have been more focused on the maintenance and operation phase. This is not surprising when you consider that an asset like a pump will be installed once during the construction phase. However, when it goes into operation, sensors could pick up operational measurements by the second and many maintenance tasks are likely to be carried out over its life. The largest amount of big data is going to be collected during its operational life.

We should not be too focused on the term big data. It is more about having all of the relevant data that you need to design, procure, subcontract, construct, install, commission, operate, maintain and dispose of the asset with the objective of maximising the benefit from the asset at the optimal cost. The focus now is about the total asset lifecycle, hence TOTEX (CAPEX + OPEX) cost is now the key financial measure. For construction companies, their primary goals are still to deliver projects faster, at lower cost, safely and at a high-quality standard. Many will also be involved in or own the maintenance or facilities management contract, so they have to consider how to optimise the whole asset life cycle. There are an increasing number of uses for digital technology to meet these very challenging objectives.

Most construction companies have poor analytical data on how a project is performing, so there is significant room for improvement. The first step is to have a solid project lifecycle business software solution in place. Then, you need to embrace all digital technologies to achieve the very tough goals demanded by asset owners and governments. Having access to real-time data can help organisations to build and maintain their assets in a smarter way through the ability to access detailed asset information; knowing exactly what the condition of an asset is, how it’s performing, its location, etc.

To survive in this digitally transforming industry, asset lifecycle organisations must first develop a digital strategy so that they can use big data and analytics to their advantage. If it they can, they’ll be able to drive down costs, reduce time-intensive tasks and increase the quality, reliability and performance of an asset through its life – ultimately securing and maintaining a competitive advantage. However, if they do not develop a strategy that includes big data and analytics, and if they continue to rely on the traditional, document-driven business processes, they will lose their ability to be agile and ultimately put their competitive advantage at risk.

Taking steps towards advanced analytics

Companies successfully embarking on initiatives like digital transformation and the application of analytics typically take three essential steps:

1. Envisioning what the organisation’s digital future will look like: This means seeing new ways that technology like analytics improve things like performance and customer satisfaction – not just trying to find an application for the technology. Problems may come through an excessive focus on the technology rather than the different ways of operating that technology enables. The vision should be transformative, not incremental, to keep it from being limited. The vision should be “the what, not the how.”

2. Investing in digital initiatives and skill sets:Getting to where you want to be will require investment. In many cases, a small initiative may lead to a substantially larger strategic investment – a step that only top executives can authorise. Understanding the need for investment, managing risk and making the necessary changes to capitalise on the investment are critical to successfully moving forward. It’s important to find the right skills to facilitate and successfully implement new tools like data analytics. Those skills may not be resident in the company. Don’t be afraid to hire new talent or turn to proven vendors to drive or manage initiatives moving the company down a data-driven path.

3. Ensuring top-down support to lead the transformation:Unless transformation initiatives have C-level endorsement – and top-down communication and corporate governance – the likelihood of success is greatly diminished. As with any change, there will be resistance to it and the application of analytics. Some ways to combat this: communicate on an enterprise-wide scale as opposed to traditional hierarchical passages, and collaborate across the organisation (think social media: forums, blogs, etc.) to encourage an ongoing conversation and get valuable insight about how employees feel and are responding.

Enterprise software applications bring a number of tools to the table to help turn change into a business advantage without complexity. For leveraging data analytics to drive operations, Enterprise Operational Intelligence software brings together solutions that visualise information to support decision-making at both strategic and tactical levels, providing insight in context when and where it is needed.

By combining enterprise architecture, business activity monitoring, intelligent business process management, business intelligence and reporting capabilities, a platform is created that allows for an end-to-end picture that is in line with the organisation’s business objectives.

What’s next?

According to IDC, “Tools to present the output of modelling are arguably one the most important elements of incorporating big data/analytics as this is where the output becomes actionable. Modelling output data, if too complex and not presented in an easy-to-understand manner, can be overwhelming and can lead to inaction, thereby defeating the underlying goal. Interactive tools that enable visual representation of modelling output data are likely to have higher success.”

These tools will lead to the rise of operational intelligence, which focuses on real-time dynamics and business analytics to providing visibility and insight into data, streaming events and business operations. Operational intelligence delivers real-time analytics for actionable decision making, through manual or automated actions.

The benefits are coming, but for early adopters, they’re here now as well. Big data/analytics solutions are working where service is the core business.

About the author:

Kenny Ingram is the Global Industry Director for Construction, Contracting, Engineering, Infrastructure and Shipbuilding at enterprise applications company IFS and a key member of its Product Direction Board. Kenny has been with IFS for 16 years and is now regarded as one of the top specialists in Project Based Business systems. See: www.ifsworld.com/au