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SAP Leonardo for Discrete Manufacturing Looks to Bring New Options for Purchasing Major Assets

SAP Leonardo for Discrete Manufacturing Looks to Bring New Options for Purchasing Major Assets

Industries such as Utilities, Oil and Gas, and Rail rely on supply chains from discrete manufacturers to build or supply the parts to maintain key assets. Traditionally, those assets are highly capital-intensive, with large investments required in equipment in order to run a business. At Sapphire Now, SAP launched SAP Leonardo for Discrete Manufacturing, which seeks to have the same impact on the discrete manufacturing business as the cloud has had on enterprise software.

The “as-a-service” designation was largely popularized by “Software-as-a-Service” or SaaS—where software is purchased via subscription rather than a license. In SaaS, the infrastructure is offered via the public cloud, so the company doesn’t need to make the initial investment in physical assets such as servers. This has revolutionized the way enterprise software is purchased, particularly in line-of-business units.

SAP is hoping SAP Leonardo for Discrete Manufacturing can have the same impact on the buying and selling of industrial equipment that the cloud has had on software.

How SAP Leonardo for Discrete Manufacturing Works

The data collected from the Internet of Things (IoT), particularly sensor-based data on industrial equipment, has the potential for huge impact on not only the way companies maintain their assets, but operate their businesses in general.

SAP Leonardo for Discrete Manufacturing is an industry innovation kit that seeks to guide manufacturers toward a pay-for-outcome model—meaning a shift from selling major assets to providing them as-a-service.

One customer example SAP has often pointed to in this sector of a company in the air compressor industry. By using sensor data, that SAP customer changed its business model from selling air compressors to selling air-as-a-service. That means its customers only paid for the air they used, rather than buying and maintaining air compressors. The air compressor company had the best insight into keeping the compressors in working order, so it took that burden off the customer.

With this new SAP Leonardo innovation kit, SAP plans to help customers help calculate risk and identify strong potential customers through machine learning, asset intelligence, and predictive maintenance capabilities. The solution will use IoT data and other contextual business information to help determine project costs and revenue to ensure fair pricing and quotes.

Finding What’s Best for Manufacturers and Industries

At Vesta Partners, we specialize in the Enterprise Asset Management (EAM) space, so we have many of the same customers as discrete manufacturers in industries such as Rail, utilities, and oil and gas.

For our customers, if SAP Leonardo for Discrete Manufacturing does what it intends, then the purchase and maintenance of major assets may be greatly impacted—going from large capital investments to pay-per-use on industrial equipment.

However, what is important to remember here is that this SAP Leonardo solution is only designed to identify those discrete manufacturing customers that are the right fit for an as-a-service offering. It may be the case that a Rail or Utilities or Oil and Gas customer finds it more cost effective to continue purchasing, rather than subscribing to, equipment.

Other times, it may prove beneficial to pay for equipment as-a-service. If that’s the case, then that’s a good thing for all parties. The important thing to keep in mind for customers of discrete manufacturers is that these changes are coming, and technology like SAP Leonardo for Discrete Manufacturing is helping to usher in that new era.

Contact Vesta Partners to find out how SAP Leonardo fits into your EAM strategy.

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SAP Leonardo for Discrete Manufacturing Looks to Bring New Options for Purchasing Major Assets2018-07-10T19:03:03+00:00

SAP Leonardo Innovation Tools: Design Thinking, Lean & Agile

SAP Leonardo Innovation Tools: Design Thinking, Lean, & Agile

SAP has incorporated design thinking as one of the key aspects of SAP Leonardo as an avenue to implementing new technologies, such as Internet of Things, Machine Learning, Blockchain and Advanced Analytics. This incorporation of a new way of solving problems goes a long way to fulfill the vision of SAP Leonardo as a way to “navigate the digital renaissance” rather than just a go-to-market strategy for new technology buzzwords. But be mindful that design thinking isn’t the end of the story. Instead, it is the beginning of a journey.

Design thinking is an excellent practice and mindset all about exploring problems and looking at the emergent solutions. In design thinking, every stakeholder is a designer and participates in creating the future. You don’t start with a preconceived notion of the solution, instead you start with an open mind and end up with something that is potentially unexpected and often great by successive refinement.

Finding inventive solutions is vital but design thinking can only get you so far. For a truly successful outcome, you need to not only come up with an innovative solution, you need to be able to deliver it.

Complementing Design Thinking

This is where other complementary practices—lean and agile—come into play. Lean thinking originated with the Toyota Production System created by Taiichi Ono, which put Toyota in the top ranks of auto production. Lean is a cultural mindset and practice that emphasizes experimentation and evidence to improve processes and outcomes using the Plan, Do, Check, Act cycle.

Agile is a mindset that originates in software development although it can be applied to other domains as well. In the late 1990s, software development had a problem: projects were failing at an alarming rate. At the time, projects were managed through waterfall project management that has distinct and successive steps for analysis, requirements development, design, development, testing and deployment. Each step had to be completed before moving on to the next one.

A Strategic Shift

That approach changes with an agile strategy. Agile emphasizes values, principles and behaviors that lead to successful outcomes instead of “one true way” that requires strict adherence to a linear process (see the “Manifesto for Agile Development”). Agile has proven to be a successful approach with strong adoption across many companies and industries because it enables better outcomes for complex projects.

Using lean techniques to test and evaluate new solutions quickly and efficiently though prototyping and customer review goes a long way to ensuring ideas that come out of design thinking are the ones that maximize value to all stakeholders. Applying lean is an efficient way to make sure you are building the right thing. Once an idea has been evaluated using lean experimentation, agile will help you build it right. The design thinking, lean and agile mindset truly enables enterprise innovation and success—and that’s why they fit so well with the new technologies attached to SAP Leonardo.

Find out how Vesta Partners Innovation Services can help you build an IoT strategy.

Post written by: Rob Ericsson

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SAP Leonardo Innovation Tools: Design Thinking, Lean & Agile2018-06-26T19:16:37+00:00

AI Overlords, or Assistants? SAP Bots are Here to Help

AI Overlords, or Assistants? SAP Bots are Here to Help

Artificial intelligence (AI) and machine learning have a great deal of potential to change the way people work. Understandably, there is great concern about the robots stealing our jobs. However, one of the first real applications of AI is to help humans work better. We see glimpses of intelligent robots helping us all the time on commercial websites like Netflix and Amazon in the form of “if you liked this, you might like that.”

These recommendation engines are driven by machine learning and are very accurate (at least for me). Although the recommendations can be unsettlingly on point, they are a big improvement in the user experience by reminding us of things we are interested in that we may have forgotten about and keep us engaged on those sites.

An AI Conversation

It is not a big stretch to see how machine learning can be leveraged in enterprise user experiences as well. In fact, SAP Leonardo features conversational AI as a way of interacting with enterprise software through the natural language capabilities of SAP Leonardo Machine Learning Foundation. Based on this foundation, you can build your own digital assistant or bot that can assist with the completion of tasks. For example, a conversational interface that helps create a new maintenance notification where the system helps a person define and resolve the problem as illustrated below.

SAP chatbot maintenance, AI, artificial intelligence

Interacting with natural language in the form of voice or simple text commands is much easier for casual users and allows for a dramatic improvement in user satisfaction by providing individual and contextual communcication. To that end, SAP introduced CoPilot in the 1705 release of SAP S/4HANA Cloud and continues to invest in bot technology. In fact, SAP has recently purchased a French company called Recast.AI to further drive the development of conversational chatbots. Considering the benefits of AI-driven software in the workplace, instead of fearing our new robot overlords, maybe we can welcome a new and more human-centric way to interact with enterprise systems.

Post by: Rob Ericsson

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AI Overlords, or Assistants? SAP Bots are Here to Help2018-04-27T19:50:42+00:00

Better SAP EAM Through SAP Fiori and SAP S/4HANA

Better SAP EAM Through SAP Fiori and SAP S/4HANA

What’s the business case for SAP S/4HANA? That varies by company of course, but those with a vested interest in SAP Enterprise Asset Management (EAM), there are some clear benefits in making the leap from a legacy system to SAP’s latest ERP innovation.

From the user experience, to analytics and the ability to extend with SAP Cloud Platform, there are key differences in S/4HANA from its predecessors. There are challenges in moving to SAP S/4HANA, though. That’s why Martin Stenzig, Rizing CTO, took to the podium in front of a packed room at SAP-Centric EAM in Austin, Texas to discuss those key topics that SAP customers should keep in mind when considering the leap to S/4HANA.

Combining Mobility and Usability

EAM isn’t commonly something that happens on one laptop or in a single location. For many industries, maintenance is done by field employees, making the challenge of entering and accessing data a challenge—and one that requires mobile capabilities.

However, simply providing mobile capabilities to field maintenance workers does not guarantee adoption. Employees have to be encouraged to use mobile applications, and the best way to do that is by providing a simple user experience that makes work easier.

“The discussion is changing. It’s not anymore about mobility and usability—it is a combination of both,” says Stenzig.

For SAP customers, Stenzig points to the SAP Fiori user experience in SAP S/4HANA as way to take traditional SAP transactions that were tougher to access in SAP GUI and put them in a more user-friendly interface. Fiori is browser-based, which means it is can be accessed on many different operating systems, allowing a field employee conducting on a mobile phone or tablet to see the same screen as their colleague back in the office who may be scheduling the maintenance.

SAP itself point to the Fiori user experience as a key differentiator in asset management on S/4HANA versus asset management on legacy SAP ERP systems. However, Stenzig does warn that a key question to ask when considering Fiori Launchpad—it does require connectivity–as an access point for employees in the field is whether or not they will have access to WiFi or mobile internet.

Read more on how asset management differs in SAP S/4HANA.

SAP Cloud Platform Vision

An important piece of SAP’s plan for how customers deploy S/4HANA is utilizing the SAP Cloud Platform as a way to augment systems that would be considered vanilla by past SAP ERP standards.

“How SAP envisions SAP Cloud Platform is to keep core S/4HANA fairly static and with a sidecar approach transfer tables you need into the cloud,” says Stenzig. “If you want to build add-ons to SAP systems, do it out there (in SAP Cloud Platform).”

Stenzig explains while this strategy makes logical sense, it’s not necessarily easy to accomplish. It’s important to have a stakeholder drive the development on SAP Cloud Platform, because if so the time to innovate is reduced dramatically.

“If you don’t do anything with [SAP Cloud Platform] right now, that’s fine, but you need to get versed on it,” he adds.

Attend one of Vesta’s complimentary SAP Asset Management workshops.

The Basis Challenge

Stenzig said the biggest lesson that SAP EAM customers considering a transition to S/4HANA should consider is the importance of training SAP Basis teams for the move. Their tasks change with S/4HANA, going from not just working with the core SAP ERP system, but to previously optional components such as Enterprise Search. Basis teams must also consider working with SAP Fiori, which means different browsers and different security certificates. There’s also the integration with SAP Cloud Platform—these are all things that Basis teams need to know.

“The challenge we see is that Basis organizations simply aren’t trained—that’s not their fault, it’s normal while going to S/4HANA to underestimate that part,” says Stenzig. “Either contract somebody, train individual people, or make it part of the contract that you already have. As a partner, [Vesta Partners] is making it a contingency to make sure your Basis people can do what is required.”

Taking EAM ‘Out of the Stone Age’

Why make all this effort to move to S/4HANA? Well first, Vesta Partners EAM Codex can make the process easier and faster, but aside from that moving to S/4HANA is part of laying the technological footprint that can enable companies to take advantage of new technologies. That means SAP Leonardo and that entails—Internet of Things, blockchain, Big Data, advanced analytics and more.

“You want to get to the point where you can talk about predictive maintenance or digital twins, but you’ll never get out of the Stone Age until you change the foundation,” concludes Stenzig.

Learm more about building your S/4HANA and SAP Leonardo foundation with EAM Codex.

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Better SAP EAM Through SAP Fiori and SAP S/4HANA2018-04-19T23:13:33+00:00

Asset Management Differences in SAP S/4HANA vs. SAP ECC

The Difference Between Asset Maintenance in SAP S/4HANA vs. SAP ECC

SAP S/4HANA® is SAP’s next-generation ERP, but here’s a little secret: Transactions in legacy SAP ERPs—such as SAP ECC—can be just the same in S/4HANA. Does that mean running asset management with S/4HANA is the same as running it in SAP ECC? Not quite, and the fact that S/4HANA is optimized to run on the SAP HANA database is a key differentiator.

“I hear comments that S/4HANA asset maintenance is the same as ECC, but SAP HANA is why certain things are only possible in S/4HANA,” says Karsten Hauschild, Solution Manager at SAP, who spoke at the SAP-Centric EAM conference this week in Austin, Texas.

The SAP Fiori Impact

Hauschild points to S/4HANA’s user experience, which is driven by SAP Fiori applications such as Request Maintenance and SAP GEO Framework. The former drives maintenance request notifications, while the latter taps into SAP ESRI to run SAP plant maintenance transactions via maps.

“The user experience from a workflow/work order perspective is vastly different from SAP GUI (SAP’s transaction code-driven user interface),” says Hauschild. “That’s from feedback we’ve gotten from current customers—that SAP GUI is ugly.”

There’s also a S/4HANA-specific maintenance scheduling application which is meant to replace SAP Multi Resource Scheduling (MRS) for scheduling individual technicians.

HANA-Driven Intelligence

The case for an improved user experience is about expanding the number of employees that can access the data in the SAP system, Hauschild adds. SAP GUI screens that aren’t part of Fiori apps have also been updated to look more like Fiori.

Beyond an interface that is prettier to look at, S/4HANA is also utilizing its in-memory database to drive embedded analytics and what SAP calls “Enterprise Search”—a keyword-based search function. The embedded analytics provide visualizations directly on S/4HANA transaction screens, while also providing automatically calculated KPIS.

Enterprise Search allows users to find transactions and information within the SAP system regarding a term—rather than looking up by transaction codes or work order numbers.

The Same, But Different

As an example of the similarities between the two ERPs, Hauschild says all plant maintenance transactions that exist in ECC are in S/4HANA, and have been since its launch. Overall, an SAP customer moving to S/4HANA from ECC doesn’t have to change business processes, it’s just the way SAP supports those processes from a user experience and analytics point of view—with Fiori, embedded analytics and enterprise search—that is different, he explains.

Now, that doesn’t mean that it will be a guaranteed breeze for customers to move old transactions onto S/4HANA—that process can still be arduous. Fortunately, that’s where Vesta’s EAM Codex solution comes into play, to speed up that transition to modernized SAP enterprise asset management.

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Asset Management Differences in SAP S/4HANA vs. SAP ECC2018-04-19T23:10:34+00:00

GIS Blog Series – Part 10: Regulatory Reporting Challenges

GIS Blog Series – Part 10: Regulatory Reporting Challenges

This is the tenth and final part in a series of blogs designed to address Geographic Information Systems (GIS) in conjunction with SAP. We will do this by addressing the most important customer challenges.

Regulatory Reporting Challenges


Regulatory compliance can take on many forms. Organizations whose asset network is spread over a large geographic area will often share common types of regulatory related challenges with regard to maintenance of an asset network such as a pipeline, electric, or rail network. This post will take a look at some of the cross industry regulatory activities and address some of the ways that integrating SAP and GIS platforms can save time, money, and ensure all operations are executed in accordance with all regulatory requirements.

Identification of Regulated Work

Organizations with an asset network that travels through different areas with specific regulatory requirements will often have business processes in place to identify and acquire the requisite permits to perform work against the assets in these areas. This could include permits required for work performed in environmentally sensitive areas, areas where a Right of Way is present, and land owned by indigenous populations. With the integration of GIS into SAP using SAP’s Geo Framework (GEF), planned and unplanned work can be rendered on a map, layered on top of regulated areas.  This work includes preventive, corrective, regulatory, and inspection work. can be rendered on a map and layered on top of regulated areas that are represented as polygon features. Work orders falling within these boundaries can be set up to have the relevant permitting operations automatically loaded into the work order, setting the permitting process in motion automatically. Not only does this save time in the permitting effort up front, it also ensures the permit procurement process is not overlooked. This type of planning can prevent crews from being turned away from work sites or avoid fines due to completed work without the required permits.

In addition to the permitting process, the same assets within certain areas may require different inspection and maintenance schedules than those outside. In these cases, preventive maintenance plans and inspection schedules can be automatically generated or updated for assets falling within these maintenance or inspection zones. For example, natural gas transmission pipeline assets that travel through areas where people tend to gather in large numbers such as schools and churches, as well as areas where population density is high, will require more frequent inspection and maintenance. As the population grows around these pipeline locations, pipeline companies must constantly reassess the population density and adjust the maintenance and survey plans manually. Bringing in the results of the population analysis from the organization’s GIS, in the form of geometry, will allow SAP to automate the analysis, adjustment, and creation of these maintenance and inspection plans. This not only saves time and effort by pipeline integrity groups within the organization, but takes out the element of human error in the adjustment of the maintenance and inspection schedules.

Regulatory Reporting

Periodic regulatory reporting imposed by regulatory bodies is a fact of life in many industries. The scale and complexity of these reports can vary widely, however the major challenges are generally the same:

  • Gathering data across multiple systems is inefficient and time consuming.

  • The data collected from the different systems, representing different aspects of the same assets, rarely line up.

  • Data in either system may be old and potentially inaccurate.

In an organization whose GIS and SAP systems operate without an automated interface, gathering the data to drive compliance reporting is only half the battle. The task of getting data from separate systems to match up can be a daunting task. The reason for the additional effort can be attributed to any number of reasons, however the most common reasons relate to the differences in the way data is maintained in each system, as well as differences in the business processes influencing the data maintenance. These inconsistencies can manifest in something as simple as a typo in one system that is not reflected in the other, to something as complex as the precision and detail at which the data is required to be stored in each system.

A common example of this is reporting on lengths of assets located within tax jurisdictions. In some cases, the length of assets are recorded and stored in GIS as the length of the two dimensional shape on a map.

On the other hand, SAP may contain a length that was calculated by the actual footage of the material installed, accounting for the additional material used due to elevation changes along the length of the asset. When trying to compare the footage of a given asset between SAP and GIS, the numbers will not match. If these conflicting numbers make it into the same report in different locations, it will give regulators the impression that none of the data is correct, spawning costly audits and possible fines. With the preceding issues in mind, reporting that marries work-related data in SAP with location-based data in GIS can pose quite a challenge.

The implementation of an automated interface between enterprise wide GIS and SAP can mitigate the pain points above by ensuring the records created, modified, or removed from one system, are automatically reflected in the other system. Looking back at the previous example, integrated systems would be able to reflect the correct geometry from GIS while pulling in the correct length values from SAP, resulting in reports that will easily reconcile between the two systems.

As long as the full set of data required by the report is shared by both systems, a user no longer has to request data from each system and combine the data into a single report, solving the second pain point listed earlier. Instead, the user compiling the report simply needs to be able to find the data in either SAP or GIS. Since there is no longer the need to go to multiple systems to compile the report, there is no longer the need to make sure the datasets agree with each other since there is now a single, reconciled dataset available for reporting.

Proof of Regulatory Compliance

Reporting on the fact that your organization is compliant is one thing, but what if you are asked to prove it? A great example of this kind of proof of compliance reporting is inspection work. Going into the field and inspecting infrastructure on a periodic basis is something that many companies must comply with. From a compliance perspective, there are rules in place that require some infrastructure to be inspected more frequently than others. These inspections are often driven by public safety and the records of these inspections are the first place investigators will look if something goes wrong. With the proper processes in place and tools in the field, proving an inspection took place when and where it was recorded is much easier to prove.

In this case, GEF opens up quite a bit of new functionality in SAP, as well as opening up new possibilities for existing tools within SAP. Work, for example, can now be rendered as geometry within GEF. This geometry can be pushed to SAP Work Manager, SAP’s mobile work management solution, giving a field user the exact location of the assets to be inspected. While preforming the inspection, Work Manager can capture the device’s coordinates at a defined interval, creating evidence of the exact location of the inspector at the time of the inspection. This data can be attached to the work order and recalled as part of the work order history. The image on the right illustrates how the location of the inspectors, during an electric transmission tower inspection, is captures and saved with the Work Order as additional proof of inspection. This data can also be used as a form of quality control within the organization to ensure the most efficient inspection routes are being utilized. This data can also be published to the GIS system, giving auditors easy access to the time and location of inspection rendered next to the relevant assets on a map.


The critical nature of regulatory compliance designates it as a high priority across all industries. Identifying, reporting on, and providing evidence of work falling within the bounds of regulatory compliance are challenges that all many organizations face. Although there are many more challenges related to maintaining regulatory compliance, we believe the three aspects of regulatory compliance outlined in the preceding post would see benefits in gained efficiencies in regulatory related planning, reporting, and audit response by the integration of SAP and GIS platforms within organizations maintaining networks of assets spread across a geographic region.


Subscribe to our Newsletter below and stay tuned on the future GIS blog posts focusing on topics such as: Data Maintenance and Data Integrity, Influence on Planning and Scheduling, Mobility, Spatial Analysis, and Material Traceability.

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GIS Blog Series – Part 10: Regulatory Reporting Challenges2019-05-19T16:35:35+00:00

GIS Blog Series – Part 9: Inability to Optimize Maintenance Routes Due to Lack of Spatial Data

GIS Blog Series – Part 9: Inability to Optimize Maintenance Routes Due to Lack of Spatial Data

This is number nine in a series of blogs designed to address Geographic Information Systems (GIS) in conjunction with SAP. We will do this by addressing the most important customer challenges.

Inability to Optimize Maintenance Routes Due to Lack of Spatial Data

The Benefits of Route Optimization

For geographically dispersed asset maintenance, travel represents a significant portion of the overhead cost to a company. The time and cost required to travel to field locations is one area where companies could suffer, or become more profitable with superior planning and route optimization. Companies are recognizing that they can leverage Enterprise Resource Planning (ERP) and GIS systems together to create efficiencies, not just in fuel consumption savings, but other areas as well. We will identify some of these areas in this blog. 

Routing Without the Spatial Dimension

Without the spatial element, routing can be planned using other factors such as the duration of the job, criticality of the asset, or regulatory priorities. In this scenario, a better term would be “sequencing” since the elements of distance and location are not taken into account. Routing, for our purposes, occurs based on the content of the work and the location of the work. Non-spatial factors are still important, but adding in the spatial dimension unlocks significant optimization potential.

Keeping the Human Element

It should be noted that in non-spatially planned maintenance scenarios, field workers often route on-the-fly depending on the way work is dispatched, and the extent to which they can self-manage. It is often a challenge to maintain the field workers’ desired level of autonomy whilst introducing improvements to the way field jobs are dispatched and executed.

In fact, there is an advantage to keeping some of the “human element” to field routing and decision making. Field technicians gather intangible knowledge about their service areas over time that can provide invaluable input into the routing process (eg. Traffic patterns, or knowledge of a reoccurring long train crossing delay). It is also important to retain some human flexibility in field execution when dealing with customer related jobs (eg. Being able to return to the job in an hour at customer’s request).

A good solution still allows for flexibility with human input.

Address Locations and Precise Geometry

Traditionally, only addresses would be used to specify job sites. The use of only addresses for routing can be problematic. As an example, the writer was riding along with a utility crew, and after turning onto the street, over 30 minutes was spent just finding the site where a meter removal was to be performed. This was due to the inability of GIS mapping software and apps to accurately identify where the address was, or a suitable ingress point. This is the nature of addressing, and it may never improve.

Furthermore, some rural locations or new construction site may not even have precise address information. Likewise, a particular asset may not even be linked to a specific address.

Properly integrated ERP/GIS systems can eliminate the inaccurate representation of job locations. When assets are created in ERP/GIS with accurate geometry (ie. Pin-point “place on earth” coordinates), the use of addresses for routing and navigating can be relegated to a secondary option.

Now, mobile maps can generate driving directions to the asset’s actual coordinates instead of an address, which may be a large spatial area in itself. Even when addresses are accurate, the ability to pinpoint the asset location within property boundaries, is highly beneficial. The advantage becomes only more profound when dealing with underground or hidden assets.

It is also important in emergency situations to route first responders to the precise asset location (e.g. Gas valve) instead of the nearest address. Addresses can also sometimes be non-unique. A number of years ago, a mid-western utility was told of a gas leak. The supplied address turned out to be problematic as there were two identical street names within the same city. The first responders went to the unaffected house first, and unfortunately a serious incident occurred as a result. The example serves to highlight the flawed nature of the street address system and its impact on the routing process and sometimes, public safety.

Remote Asset Locations

Having precise asset geolocation is also important in situations where the asset is located in remote locations that may not even be serviced by roads. Many utilities, for example, visit job sites by helicopter or all-terrain vehicles and traditional GPS unit navigation will not necessarily be useful in these situations.

A real-life example would be that of a west-coast based Utility running a new mobile app. Within their mobile application they knew the location of where they needed to get to. It happened to be a mountainous area of the state. In addition to using driving directions on the app, they were able to switch to an aerial view showing where they were located (using GPS) and where the asset was located (fed from backend ERP/GIS). Using the satellite view they were able to find an unmarked old dirt road that a vehicle could still be driven down. In this one example, the dirt road provided a considerable short cut to the asset.

Using Shapes for More Efficient Sequencing

In cases where the work being performed covers a spatial area and not just a single location, geometry can be used to optimize the sequence of work. Consider an inspection that follows a street route, such as a gas leak survey. If the geometrical description of the work is the planned route of the surveyor, then by definition there is a start and end point. If the start and end points of the job are known and stored or accessible in ERP, then they can be efficiently sequenced with other jobs by comparing the end point of one job with the start point of other jobs.

Likewise, when work is described by a polygon (eg. Vegetation work), it’s more effective to plan spatial work with accurate geometry than an approximation represented by a point.

Routing Based on Value Return

Sometimes spatial data can be mashed up with financial “return on visit” information to impact a company’s bottom line in more ways than just travel cost. Consider a Credit and Collections department of an organization that provides cable or utility service. This department will schedule and dispatch people into the field to either try and collect overdue payments or turn off services due to non-payment.

Route optimization could use criteria such as how much a customer owes and how long they have been overdue. For example, your algorithm could be designed to go after the highest owing customers first. However, if you’re not factoring in customer locations you may be sending field workers all over the service territory in an inefficient manner.

If you do however factor in location, you can now cluster customers and their potential return value. In doing this, you can create groups of aggregated customer locations and evaluate the financial impact in visiting that area on any given day. As an example, there may be a group of customers who owe only relatively little, however, they’re all residents of the same apartment complex. Traditionally these customers may not be approached for payment (or disconnected) for a month or more. With intelligent spatial algorithms, it could actually be more cost effective to send collections workers to this apartment complex.

The image above illustrates the locations and dollar range of delinquent customers. The advantage of knowing the locations of these customers allows the collections group to prioritize clusters of accounts that have higher outstanding payments due. One such cluster is circled on the map. This ensures field collection crews are dispatched to areas where the value of their work is maximized.


We have listed many aspects of route optimization, from simple fuel cost savings to turning your tabular data into powerful geospatial routing parameters. It is important to understand that these concepts are only possible with a strong foundation of integrated backend systems and accurate data. When this foundation is in place, routing becomes much more effective as antiquated addressing is replaced by highly accurate asset geometry. In the end, it comes down to perfecting your organization’s knowledge of where your assets are, and reaping the benefits of efficient work routing and execution as a result.


Subscribe to our Newsletter below and stay tuned on the future GIS blog posts focusing on topics such as: Data Maintenance and Data Integrity, Influence on Planning and Scheduling, Mobility, Spatial Analysis, and Material Traceability.

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GIS Blog Series – Part 9: Inability to Optimize Maintenance Routes Due to Lack of Spatial Data2019-05-19T16:35:45+00:00

GIS Blog Series – Part 8: Performing Spatial Analysis of Field Work

GIS Blog Series – Part 8: Performing Spatial Analysis of Field Work

This is number eight in a series of blogs designed to address Geographic Information Systems (GIS) in conjunction with SAP. We will do this by addressing the most important customer challenges.

Performing Spatial Analysis of Field Work

Since we have already covered the advantages of integrating GIS and SAP systems with regard to planning and executing work, this post will focus more on the benefits of spatial analysis as it applies to analyzing completed work.  As we have been preaching throughout the series, the ability to integrate SAP data with an organization’s enterprise GIS offers many benefits including: 

  • The ability to identify trends surrounding different aspects of asset maintenance giving management a powerful tool to identify and understand ways to more efficiently maintain assets.
  • The use of spatial analysis to help understand where time and money are being spent across an organization’s asset network. This analysis is paramount in being able to identify trends in the ways these two resources are being utilized. 
  • The location and attribute information of completed work can provide significant benefits to forensic work following any unforeseen incident within an asset network.

Let’s explore these benefits in a bit more detail.

Identifying Trends

Aggregating and reporting on the cost of maintaining a specific piece of equipment, or many pieces of equipment in a given functional location is a common practice and can be used to identify trends.  However, these reports tend to be very complex and although trend analysis using tabular reporting can easily identify spending trends for a specific equipment or functional location, it is difficult to identify trends in groups of objects that share the same geography.  Creating a spatial representation of Work Orders though integration with GIS allows dollars spent on maintaining infrastructure to be plotted on a map, easily uncovering trends and relationships between corrective maintenance and location. These analyses allow an organization to fine tune preventive maintenance schedules based on location to quickly identify chronic maintenance issues based on location, improve reliability, and ultimately save money on corrective maintenance costs. 

A popular method of displaying this data spatially is by using a heat map.  A heat map is created using point data.  In our example, we will use the location of completed work orders.  A continuous surface is created by analyzing either the density of the point features or based on an attribute value associated with each of the point features.  In the heat maps we use for our example below, the total cost of the work for each work order is used.  The example later on uses the amount of time spent above and beyond the planned time for each work order operation.

Heat map based on relative dollars spent on corrective work order operations where blue is lower spend and red is higher spend.  Looking at tabular data alone may show a list of objects with higher than normal spend, however, hotspots of dollars spent on corrective maintenance become obvious when viewed on a map and may be associated with the location in which they are installed, prompting further investigation.

Another way to use completed work order data to identify trends is by analyzing actual time spent on specific work order operations displayed on a map to determine if the location of work is affecting the time it takes to perform the same type work across a larger service area. Seeing this data visually will quickly reveal areas that require additional time due to any number of factors.  Although further investigation may be required, identification of this trend by seeing it on a map is very intuitive and far quicker than trying to find trends though complicated tabular reporting.  A slight variation on this analysis can be based on the number of occurrences over a given period which would identify whether a problem is getting worse, or better.  These discoveries can result in the adjustment of the planned time to complete specific operations on preventive maintenance plans in specific areas.  Updating plans with proven data will lead to more accurate planning, scheduling, and budgeting for work in these areas.

In addition to identifying areas where things may be going wrong, the same analysis could be used to determine where things are going right.  In organizations where different regional offices have some level of autonomy around managing their own territory and crews, trends that appear to be going in the right direction could indicate process improvements by territory managers in one territory that could be leveraged and made into a companywide initiative to improve processes across all territories. 

Heat map based on deviation from planned vs. actual time spent on work order operations where blue is a minimum deviation and red is a large deviation.  Immediately it is apparent that jobs that take place in more rural areas took longer than planned in general.  In addition, there is a clear anomaly in the center that will warrant additional investigation.  Given that there are quite a few areas where more time was spent than was estimated, the anomaly in the middle of the map would not stick out in a tabular report.  However, on a map, it is obvious.

Forensic Work

Something that we haven’t touched on much in this series is the idea of an integrated GIS and SAP system lending a great deal of valuable input to many types of forensic work.  Let’s take a look at an example from the rail industry.  In the event of a derailment, the question on everyone’s mind is “why?”.  Using asset and work data displayed in a GIS, along with reference data from other GIS sources, forensic analysts can find the answers to questions like:

  • When and what work was done in this area?
  • What known defects were present at the time of the derailment?
  • When was the last automated test run for this section of track?
  • What materials were used in this section of track?

In keeping with the environmental factors theme in an earlier blog post, answers to the following environment related questions can be added to the overall investigation to shed additional light on the root cause:

  • What were environmental monitoring devices reading at the time of the derailment?
  • Were there any recent weather/temperature events in this area?

These are all questions that will contribute to determining what did or did not cause the derailment.  With the SAP-GIS integration in place, the work-related data is readily available for any spatial analysis required to answer these questions, minimizing the time required to determine root cause.  Additional spatial analysis can then be used to determine where else along the rail line the same conditions exist, allowing maintenance crews to be proactive and address the root cause in other areas of track, mitigating the risk of an additional derailment.

In summary, the spatial analysis of completed work can greatly benefit any organization with assets spread over a geographic area.  This data will drive the identification of trends in asset failure, work order cost, and work order operation duration with relation to surrounding geography, ensuring these issues will no longer go undiscovered.  Finally, this data will greatly reduce the time spent on root cause analysis of asset related failures, including being able to take the results of the analysis and identify any other areas through the asset network with similar conditions, thus mitigating risk of additional failures and costly repairs.


Subscribe to our Newsletter below and stay tuned on the future GIS blog posts focusing on topics such as: Data Maintenance and Data Integrity, Influence on Planning and Scheduling, Mobility, Spatial Analysis, and Material Traceability.

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GIS Blog Series – Part 8: Performing Spatial Analysis of Field Work2019-05-19T16:35:53+00:00

GIS Blog Series – Part 7: Enabling Material Traceability with GIS & SAP

GIS Blog Series – Part 7: Enabling Material Traceability with GIS & SAP

This is number seven in a series of blogs designed to address Geographic Information Systems (GIS) in conjunction with SAP. We will do this by addressing the most important customer challenges.

Material Traceability is defined here as having traceable, verifiable, and complete data.  For assets, such as gas transmission pipelines this set of data could include:

  • Material attributes and manufacturer’s batch attributes
  • Test / inspection results
  • A history of inventory movements from Manufacturer, to Supplier, to Storage, to Job site, to its precise location in a pipeline network
  • Please see PHMSA excerpt at the end of this post for exact requirements

Having the ability able to quickly access this information digitally as opposed to dedicating a small team to manually search hard-copy documents is often seen as a wish list than a reality for many well-intentioned organizations.

Successful implementation of a material traceability solution involves documented business processes and cross-functional coordination.  Primary applications critical to a robust material traceability program include an ERP system such as SAP, and GIS for exact location information.  Additionally, key digital documents should be kept in Document Management System for easy access

An end to end process would include the following high level steps:

  • Establish Materials to be tracked in Batches and those to be Serialized
  • Procurement of Materials
  • Receipt and Storage of Material and Quality Inspection results
  • Consumption of batches and serialized materials via Work Order
  • Pass material and batch quantities as well as material and batch characteristics to GIS via Interface
  • As-built process in GIS mapping features and attribute values without re-keying data supplied by Interface
  • Passing of features and attribute location back to SAP from GIS via two-way interface
  • Creation / change of Functional Locations and Equipment with LAM values including batches as linear characteristics via SAP – GIS interface
  • Ability to report serial number history
  • Ability to track batch movement including return to SAP with precise location of batches throughout network
  • Use of both SAP and GIS for critical reporting
    • Serial Number history
    • Batch inventory movements and location information
    • Spatial Analytics enabling batch performance vs. location / environmental / climate factors

Role of each system in Material Traceability 

Primary Benefits:

  • Meet compliance / regulatory requirements
  • Standardize business processes across functions
  • Support where used and where in network reporting
  • Avoid usage of unapproved materials
  • Create traceable, verifiable, complete records
  • Spatial Analytics of Material performance vs. climate, environmental factors
  • Scalable solution for future initiatives


If Material Traceability was easy, many more companies would already have well-established processes.  If your company is embarking on a such a program and you own SAP and a GIS application, a robust solution may not be as far off as first thought. 

Companies must still work with Suppliers for proper labeling / barcoding of material.  Discipline must be established to track batches and serial numbers for all physical movement from receipt to storage, to job site, to precise installation location.  Even scrapped or leftover remnants must be accounted for.  Mobile devices and label scanning is virtually a must. 

The key message here is these two systems (GIS and SAP) are entirely capable of enabling and supporting Material Traceability.

Note: [Docket No. PHMSA-2012-0068], Pipeline Safety: Verification of Records

An owner or operator of a pipeline must meet the recordkeeping requirements of Part 192 and Part 195 in support of MAOP and MOP determination. Traceable records are those which can be clearly linked to original information about a pipeline segment or facility. Traceable records might include pipe mill records, purchase requisition, or as-built documentation indicating minimum pipe yield strength, seam type, wall thickness and diameter. Careful attention should be given to records transcribed from original documents as they may contain errors. Information from a transcribed document, in many cases, should be verified with complementary or supporting documents.


Subscribe to our Newsletter below and stay tuned on the future GIS blog posts focusing on topics such as: Data Maintenance and Data Integrity, Influence on Planning and Scheduling, Mobility, Spatial Analysis, and Material Traceability.

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GIS Blog Series – Part 7: Enabling Material Traceability with GIS & SAP2019-05-19T16:35:59+00:00

GIS Blog Series – Part 6: The Challenge in Linking Asset Health to Environmental Factors

GIS Blog Series – Part 6: The Challenge in Linking Asset Health to Environmental Factors

This is number six in a series of blogs designed to address Geographic Information Systems (GIS) in conjunction with SAP. We will do this by addressing the most important customer challenges.