In an industry that is in charge of billions of dollars of assets, it’s crazy think that the current approaches to asset management are so far behind the curve.

For utilities, which manage facilities, pipes, lines, valves, meters, and many other physical assets, the need to adopt technology to prepare for the financial future couldn’t be greater.

Currently, asset management strategies are largely based on two approaches:

1. Inventory your assets- understand what they are, where they are, how old they are, and any other basic data. Put that into a software system (GIS, CityWorks, Lucity) so they can be visualized and managed.
2. Manage your assets (repair, replace, etc) based on their age– look at a typical or assumed end of useful life curve to figure out what to repair or replace. In other words, assume that an underground pipe is 50 years old and should be replaced in 10 years, because they last about 60 years total.

What’s the problem with this approach? It facilitates throwing massive amounts of money out the window! If an asset is replaced before it’s end of useful life, or isn’t replaced before a major failure, it will cost your organization money that could be prevented with strategic asset management approaches.

So what is the winning strategy? Managing your assets based on their condition, risk, and cost. What does that entail?

Condition– In other words, understanding the true condition of an asset before deciding how to repair or replace. Forget just relying on age- understand the condition (good or bad) of it before making a decision. Do this by looking at the age, the composition, the conditions surrounding it, and any other factors that could extend or shorten it’s like. Great example is an old car- do you need to replace an old car in great condition, just because it’s old?

Risk- Assets fail, so make sure to manage the highest risk assets. Which assets are critical to a system? Which assets would cause great financial impact to an organization if there was a failure? Prioritizing asset management based on the highest risk assets will ensure major risk reductions and optimization of repairing and replacing the right assets.

Cost– What are the costs to replace, reduce risk, and to optimize decisions? Organizations need to be able to quantify this for planning and day to day purposes. Speak the language that all of world speaks- money!

Using these principles for asset management will help organizations make smarter decisions, reduce risk, and save money.

Often times enterprise software systems come in “modules” that offer functionality to serve multiple business groups, departments, or processes. Examples include:

• Requirements
• Contracts
• Safety
• Objectives
• Risk
• Procurement

Often times in the sales process, multiple modules will be offered together in a package deal, to increase value and bring more users into the best practices provided by an enterprise software system.

Makes sense, right?

Of course! Only buy the modules that you need. And expand into different modules once you’re ready (and once the department, group, or business function it serves is ready).

But a very prudent question to ask is how are these modules connected? How is data shared between Contracts and Risk? How can we roll data up across all of our modules to support our corporate goals and objective tracking?

It’s a pretty logical to assume that it would be straight forward and easy to make modules talk to each other. However, often times modules don’t talk to each other at all, and require quite a bit of work to connect- even though they are from the same platform, company, and system.

If you’re looking into an enterprise system with multiple modules, consider these questions:

1. Do the modules share a single database– if yes, this should make it easier for the modules to “talk” to each other and share data
2. Are there any integrations required to share data between modules– if so, there could be additional software costs (adapters, servers, etc) and service costs (technical consulting to install the modules)
3. If an integration is required, how is it set up- are there any pre-built adapters to make the integration easier? Is data shared through XML/batch files or is the integration real time? What data fields can be exposed?

Asking these questions can save you a lot of time, money, and headaches.

As a solution consultant and sales engineer within the enterprise software space, I am constantly asked by clients one key question:

• Can I create [XYZ] report?

This is such a rational, legitimate question! After all, what’s the point of an enterprise software platform that collects and aggregates data if you can’t generate the reports you need?

Hopefully the answer to this question is “Yes.” Well developed, well thought out systems can facilitate the aggregation, roll ups, and slices and dices of data in multiple ways with ease. Want to compare how department A is performing against department B? How about instead of comparing department A, we compare Program 1 to Program 2? What about rolling up transactional data in more than one vertical across the company?

The possibilities really are endless in the way clients want to report on their data. And they have every right to! However it can put some enterprise software systems in a bind if their data structures aren’t carefully designed.

This is a result of using excel spreadsheets before the implementation of a enterprise system, where data structures aren’t enforced. Referencing cells in formulas is quite a manual process, however it provides users with a lot of flexibility to facilitate aggregations and calculations. However this can get pretty complicated for many enterprise systems to replicate. It becomes almost impossible for a system with poor data structures.

Here are some questions to ask when investigating data structures of enterprise software systems: 

Are reports configurable or do they require custom development?

As discussed in my previous post, you want a tool that is configurable, not customizable. This will save buckets of money on development costs and allow non-technical users to operate and administer your system. If reports aren’t configurable and require custom development, reporting will be a nightmare.

Does the vendor have a reporting team? 

There will always be some reporting requirements that stretch any system. However if the vendor has an entire reporting team dedicated to running SQL scripts to pull client reports, that may be an indication that reporting may not be as simple and straight forward as previously thought.

Does the system have multiple types of database objects? Can they be related?

Well designed enterprise software systems have multiple database objects at varying levels of detail. These systems will also allow users to associate multiple object types together. Sometimes reports will require associating object A with object C, while others will require associations of object B with object C. If an enterprise software has only a couple of data objects that don’t talk to each other, creating reports could be impossible with a custom SQL script.

Can transactional data be tagged with multiple categories?

Tagging transactional data with multiple categories allows users to tell the system where they want the data to go. If an enterprise software system does not allow you to tag data with more than one transaction, roll ups across departments, programs, regions, and more will be extremely difficult.

After working with numerous enterprise softwares over the years, I am commonly asked by clients to distinguish the difference between software configuration and customization. Both have their challenges and benefits:

Configuration means an end user (someone who is not a developer) can build, alter, and to an extent customize an enterprise software to match a client’s needs and business processes. Enterprise softwares that allow for configuration usually have a somewhat easy to use back end interface that an administrator, consultant or designer can access to alter settings as needed. Most modern enterprise softwares are built to be completely configurable. Some might argue that configuration limits a customer’s options during an implementation. For some software platforms this is true- however if the software has a solid, well developed architecture the system can be configured to match any client’s needs.

Customization usually involves developers that implement or build code for an enterprise software. Customization can be expensive as it requires constant maintenance and hiring highly skilled workers. However, sometimes customization allows a client to implement a system that fits their requirements exactly as needed.

In the sustainability space, I am sure many of you have heard quite a bit of chatter about Life Cycle Assessment, also known as the practice of modeling a product’s environmental impacts across it’s entire life span.

This practice is important for a number of reasons- reducing environmental impacts, trimming down the size of your Scope 3 carbon portfolio, etc. However, at the end of the day, it all comes down to product marketing.

Corporations are catching on to this highly technical, highly advanced practice because when conducted correctly, LCA’s are the basis for EPD’s- also known as Environmental Product Declarations. I won’t go into a ton of detail (please contact me if you have additional questions), but EPD’s allow you to make environmental marketing claims about your product compared to another.

If an EPD of a smartphone was created, reviewed, and accepted by a verification body, it could allow Apple to say that their iPhone is more green that a certain Android phone, and visa versa.

Along with the branding, nutritional facts, labeling, and (especially) pricing, sustainability metrics will be another way for a consumer to choose between products. And EPD’s, supported by Life Cycle Assessment, and Life Cycle Assessment software tools and data, will be the catalyst for these sustainability metrics. But as I described above, practicing LCA with the correct approach can be challenging.

Additionally, making marketing claims against a competitor can be risky for any brand. Claims needs to have substantial evidence and be validated with extensive data and research. Nobody likes a lawsuit!

This is why having reliable, accurate, and updated data is absolutely crucial when conducting LCA studies with the objective of making a marketing claim.

And in terms of LCA data- the data that powers these studies- there is a lot of questionable data!

While I won’t identify the ones to think you should avoid, here are the scientifically backed LCA databases one should consider:

• EcoInvent
• US LCI
• GaBi Databases (Disclosure: I work for PE INTERNATIONAL, the providers of this data)
• ELCD

Have questions? Feel free to contact me!

Please keep in my mind that these opinions are strictly my own!