DROWNING IN DATA GASPING FOR INTEL. Finding the single source of truth in information assets

Transcription

1 DROWNING IN DATA GASPING FOR INTEL Finding the single source of truth in information assets

2 The interface between engineering, design, asset management, organization and information technology is becoming more and more complex. Within this realm, can you achieve a single source of truth to help you understand your assets? Recent research undertaken by the University of Adelaide has shown that organizations demonstrate governance and management proficiency in the administration and deployment of their Financial, Human and Physical assets. However, that same research has shown most organisations have failed to implement the accountability, frameworks, management structures and measurement required to effectively deploy the other vital input to their production process, namely Information Assets. We all understand that our information assets are a vital component to enable informed decision making around operations, projects and whole of life performance of our assets so why are the potential, tangible benefits from improving their management seldom realised or harnessed appropriately. What are the barriers? In February 2018, we invited leading thinkers in asset management, covering road, rail, buildings, and technology, to workshop what they viewed as the single source of truth, its value to them, its application and its governance. This paper summarises the key discussions, insights and key questions raised during the workshop, and seeks to empower information asset owners to drive change within their organization. 3

3 THE SINGLE SOURCE OF TRUTH What is the single source of truth? One key issue to defining the single source is determining who owns the various data sets and what truth means to them. For example, is it a truth related to capital expenditure or detailed engineering design? Once you identify these sources, the challenge then becomes educating those people that they are data owners. Often the single source of truth is limited as there is inconsistency across the built asset industry in how contracts stipulate you must capture data. Does a single source of truth require a single data set? Should it be verified by other data sets? How do you find the single source of truth? It used to be easier to have a single source when there were limited sources of data but now that there is more data collected, it becomes increasingly difficult to determine what is relevant, what is accurate and what should be the single source. To find a single source, it is critical that you first learn how to articulate to teams what data is, how you capture it, and then how you ask various stakeholders for it. When finding a single source for large assets, it s important to understand the system that assets operate in and what the boundaries are around that asset. For example: If finding the truth of a bridge, have you considered the competency of those who maintain it? Where does the asset begin and end? What types of data do different stakeholders within the organization need from the asset? When analysing data, it is important to identify structured data (formally captured in ongoing processes) and unstructured data (e.g. captured by foreman ad-hoc on site). Even simple filters over data must be reviewed closely, for example, geography can mean different things to different stakeholders, GPS is not accurate over longterm, etc. Often third-parties may have a stronger grasp of your asset than you do. For example, large car manufacturers will have detailed data and a better understanding of roads than the road managers. 5

4 ANSWERING QUESTIONS AND TELLING ASSET STORIES What are you trying to solve with data? It s critical that you always remember that the question you are trying to answer is never static. For example: The relationship between the age and condition of an asset, soil and weather will change over time GPS as location will move over time Once you address one problem it may have flow-on affects to other parts of the asset For the story you re telling with data to be effective, you must always make sure key stakeholders, such as your Executive Board, are never surprised by what the data says. It s an ongoing conversation. Do you need to change how you view data within different parts of organizations? It s important to focus on the outcome you want to achieve before you collect vast, and potentially useless, data sets. If your ultimate goal is to improve passenger comfort, then you should capture data in real-time to determine when passengers are uncomfortable so you can then find trends and pre-emptively address passenger comfort issues. The same data and insight will hold varying levels of value pending who or which section of the organization is looking at it. This value may also change over time, as some data may lose importance and relevance as it ages, while other data will remain timeless. The way to frame the story with data insight is critical. For example, 40 bridges that need to be replaced in 10 years time can sound alarmist and a large capital outlay. It is more effective to frame it within the context of the data: we have 400 bridges under management, here is their lifecycle and predicted degradation based on data, therefore we ll need to update these 40 bridges over the next 10 years to remain operational. 7

5 BARRIERS, RISK AND ROADBLOCKS One of the biggest risks many large organizations face is that data and asset insight is kept in the minds of an ageing workforce and not recorded. For example, if there is torrential rain a senior team member will know exactly where on site the water will build up and what flow-on effect this will have to the rest of the asset. Some organizations are addressing this by partnering graduates with senior engineers who are close to retiring, however, it s crucial that the graduates capture what they learn to avoid perpetuating the issue. Trust must be built, so that we move from trust in the human brain to trust in the information asset. A lack of curiosity is holding many people back from recording what they know or asking the right questions of others to capture key intel, which can be made worse when roles and accountabilities are not fully understood. Many people who own critical data will only view the value of their data through their own niche perspective. Silos in large organizations are one of the biggest barriers to effective data and insight sharing. Breaking these down and centralizing (where appropriate) data collection is invaluable. A barrier to this can be the wrong people are in charge of the allocation and distribution of data. Has the internal organizational conversation changed? This signals the end of an era in which decisions were based on past experiences or on professional intuition decisions in the future will be based upon increasingly on a combination of historic, real time and analytically based data there will be a significant increase in the transparency and quality in the decision making process A common (misguided) argument against real-time data capture is you used to be able to manage without all this data before, so why do we need to capture it now? We have new data and new technology but often face the same old problems. What are the barriers to achieving a single source of truth? When looking at large and complex asset integration scenarios, such as railway systems, port terminals and even cities, the assets are constantly moving, making it difficult to capture accurately. Systems must be real-time for the data to have ongoing value. Educating teams on opportunistic data capture is key identify crowd-sourcing opportunities, such as if someone is going to site, then ask them to report on a few specific parts of the asset you need to know more about. The requirements of using data are far more refined than ever before, with real-time data capture and analysis becoming more and more important. The challenge of appropriately capturing data is far larger than it was 20 years ago when you could call the foreman on a landline and get all the information you needed. 9

6 GOVERNANCE IN DATA WORLD Why do you need to address governance? The key issue is a lack of business/corporate governance of the information and knowledge asset. This appreciation and accountability needs to be established before we can move to effectively taking data to next stages of analytics and AI if we don t appreciate the cost, value or benefit of our data information we will not appreciate its potential. Without a strong and appropriate governance model, you won t be able to capture data in a meaningful and ongoing way. One of the more difficult questions to answer is how do we govern the data that we generate? If we re drawing in third-party data sources, how does that fit into our model? Setting up proper governance and drawing relevant data out of an organisation is ultimately a change management process. It s important to understand that asking people to change proven processes can result in significant internal issues if not properly managed. It s about asking the right questions of the right people. What barriers are there to effective governance? Governance in large organizations often drifts into silos. These must be broken down, or bridges built between, to ensure the sources of truth are drawn out. If you don t have an enterprise-wide view of how the organisation works and how data is captured, then there are no escalation paths if issues arise. Organisation safety barriers are often a significant hurdle to overcome. Different people will inherently have different motivations and priorities. It s easy for people to go off and do their own thing nothing is achieved without strong governance around information assets. How do you ensure governance is effective? There are several specific actions to help governance processes remain effective. For example, updating corporate policies to allow for mobile phone use on sites to capture data, and updating security polices to use cloud-based solutions to capture, share and analyse organisational data. How you organise an asset is an important early step. Do you view it as one large asset that is comprised of several smaller subassets? Do you have a spatial view of the asset? How do you compare different datasets within the large asset itself? One practical way to move towards a single source of truth is to enforce policies to remove convenience copies of data, i.e. copies of designs, reports, spreadsheets that individuals save to desktops, rather than central systems. One company reported having over 800,000 engineering files that included 300,000 duplicates. 11

7 THE FUTURE DATA AND ASSET MANAGEMENT How can technology help you reach a single source of truth? Currently the cost of digitising large assets, for example public infrastructure, is far too high and prohibitive. Is there a horizon ahead where technology can cost effectively analyse and digitise your assets? When looking at how technology can improve asset data it s important to understand what outputs you want to achieve before you look at the technology as a solution. It will be increasingly important to have a tailored approach, the power and availability of data appears to be almost endless (similar to an engineering solution, you can build anything, it all depends how much you want to spend). Similarly we are beginning to be inundated with endless data which we can drive a number of solutions, so it is critical to have a structured process to understand the requirements, prioritise the solutions, then combine technical knowledge with functional knowledge, data and data techniques to drive the solution Bite small chunks at a time, step by step, sprint by sprint i.e. think big but start small and upscale latter, and apply a phased approach to achieve optimum asset management through combination of information asset management governance What do you do once you have the data? Once you have made the next step with technology and start to own and analyse data, you then need to look at what skills you will need in your organization, such as data scientists. The alternative is to collect the data and make it open source to promote collaboration, so that you own the data but not the how of its analysis. If you understand what data you have and can analyse it, you can then predict outcomes so that instead of reacting to issues such as asset degradation, damage or failure, you can predict and proactively address potential situations. and optimum utilisation of data value One effective way of using data to predict future issues is to analyse and identify exceptions, so that you can identify what s not normal, rather than attempting to analyse everything. What is needed for optimum utilisation of data value sound knowledge of your business and value in your organisation, functional knowledge and performance requirements, professional and accountable data management and governance, understanding the end user and the level of visualisation and reporting that support their decision making needs. What role does security play? As we gain easier access to data, security will become more and more important in the future of asset management. Security becomes complex when working across a multi-national organisation. You must have a strong understanding of the different regulations across the different regions that you operate in and where your data is stored. There are two main philosophies around data. 1) Security needs to be tightened 2) Open source on the basis that it is impossible to totally secure data (everything is hackable) rely on trust and transparency to increase potential for innovation and optimise the result (i.e. outsource all data and let the data analytics find what you didn t know you had) When looking at public infrastructure, given it is critical infrastructure to city management, it must have the highest levels of security and comprehensive protections and policies in place. What you capture internally and what you can share externally is becoming increasingly clouded. This can also affect sharing data within an organization if it crosses international borders or uses third parties to transfer data. When autonomous vehicles become available it will place a significant strain not only on the security of commuter and asset data but the governance of the data. By necessity, there will need to be a realtime single source of truth for autonomous vehicles, roads, and traffic lights (to name just a few) that can be relied on. 13

8 RELATED REPORTS ABOUT ARCADIS Arcadis is the leading global Design & Consultancy firm for natural and built assets. Applying our deep market sector insights and collective design, consultancy, engineering, project and management services we work in partnership with our clients to deliver exceptional and sustainable outcomes throughout the lifecycle of their natural and built assets. We are 27,000 people, active in over 70 countries that generate 3.2 billion in revenues. We support UN-Habitat with knowledge and expertise to improve quality of life in rapidly growing cities around the world. TACKLING COSTS IN THE DIGITAL AGE INTERNATIONAL CONSTRUCTION COSTS REPORT 2018 AUSTRALIA PACIFIC International Construction Cost Report 2018 Mobility Orientated Development Report 2018 Sustainable Cities Mobility Index 2018 City Resiliency Tall Buildings Sustainable Cities Index

9 Clara Tetther Infrastructure Advisory Lead T E clara.tetther@arcadis.com Arcadis Australia Pacific is a leader in built and natural asset design and management. From major road and rail infrastructure to innovative waste, water, residential, retail and heritage projects, we strive to create smart, sustainable solutions for our valued clients. Arcadis Australia Pacific Arcadis. Improving quality of life.