Making change predictable

Net Zero. It’s a big ask. And fairly overwhelming to comprehend. Break it down into its component parts. The Greenhouse Gas (GHG) Protocol offers a good place to start, which considers how organizations can look holistically at their carbon emissions internally and across the supply chain, from both CapEx and OpEx perspectives.

• Scope 1: direct emissions from owned or controlled sources.
• Scope 2: indirect emissions from the generation of purchased electricity, steam, heating and cooling consumed by the reporting company.
• Scope 3: all other indirect emissions that occur in a company’s value chain.

Beginner

You’re making two dimensional decisions. Decisions based solely on a clear financial difference. Doing X costs me Y and delivers me Z.

Intermediate

You’re already adding in a new consideration, in this case carbon, alongside just providing a service. A non-financial value is already part of your decision making. This could be reflected in a simple, siloed way: should I replace all lightbulbs with LED? Should I invest in carbon offsetting to get to net zero goals? You’re including sustainable criteria, but you’re still making single criteria decisions.

Advanced

Very few organizations are advanced in their decision making, but the most mature, leading companies make multi-criteria decisions, where strategic thinking is clearly influenced by SDGs, and long-term choices are evidenced-based. These companies factor financial and non-financial benefits into decision making.

At this Advanced level of maturity, you might trade off a decision to invest in new IT hardware with a decision to invest in biodiversity. You could conclude that the overall, bottomline and societal benefit of biodiversity investment is greater than that of an IT upgrade - strategic thinking is evidence-based and organization-wide.

Of course, this level of advanced decision making depends on great data. And having - and critically using - decision support tools to read and respond to it. In and of itself, a mammoth undertaking, and digitalization should be all about agility. Organizations should look for more ‘chunkable’ technologies—asset management apps that digitize specific processes or target specific challenges. These apps bring data together in consistent, useful ways, and you can get to work with them quickly.

The Six Capitals (Value Framework) is key to understanding the long term, financial and non-financial value of investments—their true value. It helps you make choices that are most appropriate for the whole environment you’re operating within.

It shows you the wider implications of investments. In terms of sustainability, Natural Capital consideration is critical. It will typically encompass carbon accounting, and other elements, to highlight the environmental cost of CapEx and OpEx decisions.

Individual elements within the six capitals, the services measures (business objectives or customer requirements) placed against them, and the cost of each, are unique to each business. But once they’re quantified, you can optimize and re-optimize measures against each of these constraints, and see how dialing up or down one measure impacts another.

In terms of sustainability specifically, this might lead you to create, for example, a more sustainable drainage system—a path around a river, rather than a new concrete tank. Great sustainable value, but a really positive impact on the human and societal elements too, and the intellectual capital of the organization. You can read about our work with Yorkshire Water for some more practical insight.

Circular processes for a circular economy — the continual use of resources to eliminate waste. While boardrooms need to make more public statements about Environmental, Social, and Corporate Governance (ESG) credentials, investors are also looking to confirm that ESG principles are thought through as part of an organization’s decision making process. They should be embedded from boardroom to operations, and back again.

Tactical asset management decisions around issues like waste minimization, resource optimization and reuse, and overall effectiveness, are key to proving and improving your credentials in the circular economy.

If you’re just starting out on your sustainability journey, start by spotting and fixing existing ESG inefficiencies. Targeted, sector-specific apps can help you use the resources you already have more effectively—minimizing waste and maximizing production efficiency. You don’t need to jump straight into company-wide initiatives and change management programs. Begin incrementally, one step at a time, and improve continuously.

Because irrespective of how good you are at ESG, there’s always more you can do.

We see a lot of disconnect from boardroom to the job site. It’s common, but doesn’t have to be inevitable. Putting processes in place to simply reconnect what’s going on operationally with what’s envisioned strategically can have a hugely positive effect. This can be as simple as visualizing and thereby revealing the strengths and weaknesses of control and mitigation measures.

One piece of analysis we at Gen previously carried out discovered an organization had a ‘governance meeting’ credited with mitigating $2.8bn of asset failure... that must have been an epic meeting! Revealing this vulnerability enabled more practical controls to be identified and disseminated.

Digitalizing processes naturally means everything is tracked, and can be more easily aligned to corporate goals. Using data to inform decision-making gives everyone from CEO to engineer access to the same insights, puts them on the same page, and ensures they’re working to a common goal. Workforce organization, driven by data, is key.

Often, organizations are operating on historic precedents. They’re reacting to issues or conforming to a static plan, and that’s how the workforce delivers tasks. There are incredible opportunities for efficiency to be found here: reacting is shown to cost somewhere between 3 and 8 times the overall cost of planning and being predictive.

Assess how you bring teams together and disseminate high level decisions, to work out what needs to be done, and who will do it. Getting those communications in place—daily, weekly, monthly—is a solid first step. Finding ways to automate them takes you further. Once a process is automated, it gathers data—and you can start making predictions.

We know how quickly and often you need to re-plan and reprioritize today. Having tools in place that let you quickly see the impact of resource reallocation means deploying maintenance teams rapidly, knowing they have the right information and tools, and are doing the right work at the right time.

And because the cost of being reactive is so much more than planning ahead, there are big savings to be achieved—between 10-40% depending on how disorganized you are in the first place!

Most organizations don’t hold data in a singular, accessible location. This is a problem. They lack the ability to examine consistent data across the business - it’s disparate, it’s unstandardized, and it has a big impact on communication and decision making.

This single issue is holding so many organizations back in their digital journey. Quantity and quality of data is seen as the most significant barrier to digitalization.

But every organization needs to start somewhere. And the good news is, you can start to make progress with what you’ve got. There’s a lot your existing data can tell you, even if it’s not the most mature dataset on the planet.

Getting value from the data you already have is the first step to more and better datasets overall—simply by collecting it together and starting to cleanse it—filling gaps, removing errors, eliminating inconsistencies.

Get it together

Stop struggling with disparate spreadsheets. Hard to maintain individually, and impossible to easily combine. A perfect recipe for inaccuracies, inconsistencies, and data that gets old, fast.

Cloud-based software creates a common pool of information that is updated on every front every time an edit is made.

Access to field data is key. Mobile collection and maintenance enables organizations to realise the utility of data, keep it up to date, keep people safe and let them be effective in their roles.

Prioritize useful data

It can be difficult to know which data silo to tackle first. A good place to start is by prioritizing data collection that is most useful to corporate targets. Say your goal is carbon reduction, start with understanding how replacing or refurbishing assets will impact this. Do your replacements have net zero production targets?

Fill the gaps

Identify where your weak spots lie. Specific, targeted apps can help you visualize data, so you can see problematic areas very quickly and prioritize data collection in those areas.

Make assumptions

It is fair—and important—to make assumptions based on the best data you have available. If you have data on the age, design life, or installation of a pipe in one area, city plans can tell you how far to extend that information to nearby assets. Flag these assumptions for later validation.

Build and refine from there!

That means pulling data together from across the organization and putting in processes that will enhance it. Evolve maintenance processes so that when that one pipe is repaired, material and condition are noted and any assumptions made can be confirmed or updated.

Now you’ve established your dataset, predictive analysis tools really come into their own. Your data’s just the first step—decision support tools built specifically for asset management companies can now really show organization-wide benefits.

Let’s take an example. You need to justify a set of investment options, with a target of carbon reduction. Our analysis shows that predictive analysis typically reveals c.20% of carbon efficiency savings, either in selecting a better mix of interventions or considering the order in which things are done.

• Once you’ve gathered and cleansed your data, you need to assess resources. Do you have the people to manage and support the targets? Will the supply chain manage?
• Then you can add your constraints. Do you have the budget? What is the timeframe?
• Of course, they’re all competing in different directions. So you optimize.
• Decision support tools will then let you model what-if? scenarios—compare pre- and post-investment outcomes.
• And finally—output and present. This is where a common data language shows real value—true evidence-based decision making and consistent thinking at every level.

Targeted asset management apps help you evolve incrementally by supporting each of these specific steps, making digitalization more manageable, more incremental.

And once you’ve taken those decisions into the real world, the beauty of digitalization is that you then get continuous feedback—and with it, opportunity for continuous organizational improvement.

A big part of digitalization is cultural. There needs to be a recognition of the importance of data as an asset—one that needs maintaining in the same way as any other asset.

Big bang initiatives that collect and improve data quality without that understanding, or with no ongoing custodian, don’t work. Everyone needs to buy in to why you’re collecting data, and how to use it. Without this commitment, data very quickly becomes outdated, inaccurate, untrusted—and stops being used in decision making.

It’s important to build that mindset across each business unit, and the organization as a whole. Each user should know their role in the maintenance and use of data. Products with structured workflows encourage this, helping your teams understand what they need to do and when it needs to be done. You need to balance process, people, tech and data—none of those things in isolation will get you to the point of digitalization.

Customer perception is a team sport, everyone in an organization has a role to play and there’s no job too small to have an impact.

• At an operational level, you’re the face of the company when you visit a customer. How you present yourself has an impact on how that customer perceives you, and by extension, the company.
• At a portfolio level, your impact on customer perception lies at the community level. How you manage major projects—their social, environmental and economic impact. How maintenance is organized and carried out. How you consult locally and whether voices are heard.
• At board level, if you’re seen to be repeatedly doing harm to a community, that becomes a clear leadership issue. If this perceived harm is avoidable, then of course avoid it, but you can mitigate unavoidable reputational issues by dialling up commitments elsewhere. By carbon offsetting, for example, if the issue is environmental. Or through local employment schemes if a specific project is badly perceived.

To truly understand and improve customer perception, you need to quantify it. You need to understand the value customers place on different service measures, so you can dial up and down accordingly.

Customer value frameworks do exactly this. They ask what’s important to customers, and quantify priorities by understanding the value placed on different service measures.

Taking a water company as an example—compare the customer perception impact of a pollution event or losing water to their home. A customer value framework measures how much value customers place on each. Having had that discussion, you can monetize customer perception, and link it back to investment decisions.

Organizations understand risk management and risk assessment. However, understanding high impact, low likelihood events is more difficult. It’s easy to imagine a pump breaking or a pothole occurring in the road, it’s harder to imagine catastrophic failure, a cyber-security attack, or a natural disaster. But these incidents are becoming all the more familiar. From power outages in Texas, to flooding in Australia, they’re happening now, they’re highly public and while they can’t be predicted, they can be prepared for.

Organizations need to think about longer term hazards and threats, as well as immediate risks. They need to think about likelihood and consequence, and how prepared their assets are to cope. Here’s how.

Identify the issues

Use established frameworks such as the J100 framework to identify the range of hazards to plan for.

Consider the consequences

Next, consider the consequences of those hazards. What would a flood cause to fail? How would a natural disaster impact a certain plant?

Plan the response

Then, explore the variety of responses available. How are you going to recover? You might not be able to say when or where a catastrophic event will happen, but you can determine how to respond quickly, and how you’ll provide the best possible service to all impacted parties.

Identify your vulnerabilities

Build resilience into your systems. For example, you identify an area at particular risk of flooding, or an area with hard to manage vegetation—how do you invest to build resistance into that specific area of your system?

Digital security is ever more critical to customer perception. As data continues to proliferate and processes become more dependent on it, it will only gain importance.

In the US especially, there’s been a huge recent focus on security breaches and data penetrations. Customers are increasingly interested in how their own data is used and protected, as well as cybersecurity—and threats to it—more broadly.

Take the recent SCADA hack at a Florida water plant. One of the major issues cited in the breach was that the facility was running an “outdated Windows 7 operating system”. Critical infrastructure must be managed carefully. If someone can penetrate sensors, monitoring equipment, controls—they can adjust set points and change the environment. Consequences could be catastrophic.

Resilience assessment is critical to understanding how robust your control measures are, visualizing them for teams, customers and stakeholders, and planning improvements in the control environment. Improvements that might just keep you out of the headlines.

Spreadsheets

Have vulnerabilities. They’re subject to human error, local access and lost laptops. How can you ensure absolute security in the hands of multiple end users?

Proprietary software

Business-built software can be well tailored to your organization’s unique needs, but, for any software that is hosted, you have to consider penetration testing, auditing, staying up to date with patches and updates, adhering to compliance as it evolves.

Third party tech

Third party tech lets you act and deploy quickly, because you don’t need to constantly test and secure your solution—your provider has taken care of it. Cloud-hosted solutions should be robustly tested, benefit from state-of-the-art security and remain constantly updated. Of course, ‘big tech’ is often too broad to be immediately beneficial, which is why it’s useful to look for more targeted, sector- and challenge-specific apps.