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Category: Artificial Intelligence

6 Ways AI Can Level Up Your Commercial Service Business

As service businesses across industries strive to innovate and maintain competitive advantages, AI technology offers unprecedented tools for enhancing service delivery, optimizing resource management, and elevating customer interactions.

At the 2024 Digital Wrap Conference, ServiceTrade VP of AI, James Jordan, provided insights into how AI is reshaping the commercial service sector. His presentation highlighted the potential of AI to drive improvements in business operations and customer satisfaction. Inspired by his talk, this article delves into six core ways that AI can level up you business.

1. Enhanced Customer Interactions

AI can revolutionize your customer’s experience with:

2. Operational Efficiency

AI can enhance operational efficiency in several key areas:

3. Proactive Maintenance

AI’s predictive capabilities can be very impactful for proactive maintenance:

4. Data-Driven Decision Making

AI can power decision-making with data-driven insights:

5. Cost Reduction

AI can drive cost reduction through:

6. Competitive Edge

AI provides a competitive edge by:

I believe AI is here to stay, and that, on the whole, it will be a positive force for good, for growth, and for value.” – James Jordan, from his DWC presentation, “Amplify Your Advantage with AI”

As James’s presentation convincingly showed, AI has the great potential to become a core component of modernizing and advancing commercial service contracting businesses. From improving customer service to reducing operational costs and gaining a competitive edge, AI offers a comprehensive suite of tools for businesses to thrive in a digitally driven world.

Learn more about ServiceTrade’s AI-powered capabilities.

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March AI Prompt of the Month: Predicting Repairs by Identifying Trends

AI is really good at parsing through a lot of data and identifying themes you might want to pay attention to. To test that out, I threw an export of the last two month’s of deficiencies from a demo Mechanical account into ChatGPT and asked it to help me prepare for the upcoming quarter by identifying any trends in the data.

As you can see, it had a little trouble analyzing the data, so I tried to help it out by giving it a link to our Support article on deficiency creation. But honestly, I think it would be better to give it a little more instruction on the deficiency data you consider to be the most important. That can be unique to your business processes, so try this out, but always remember that if you don’t get a quality answer the first time, give the AI a little help by explaining more about what you want, and also what you don’t want, and try again.

The best part about the relatively long analysis included below? It took about 30 seconds to generate and it cost me zero dollars. So tweak, iterate, and re-try, and when you finally DO get what you want, make sure to save it as a prompt template somewhere so that you and your team can use again next quarter!

The Prompt:

I work as the service manager for a commercial mechanical company. I need to plan out the next quarter by predicting repairs for customers. Analyze the attached data that shows all deficiencies reported in the past two months, and look for trends so you can generate a plan to address predictive issues. You can learn more about what deficiencies mean to me in this Help Center article: https://support.servicetrade.com/hc/en-us/articles/16143205860371-Creating-and-Managing-Deficiencies

The Output:

The data contains several columns that may be relevant for analyzing trends and predicting future repairs for your customers. Here are some key columns in the dataset:

To predict repairs for the next quarter based on these deficiencies, we can analyze trends such as the most common types of deficiencies reported, the frequency of reports over time, and if certain locations or types of assets are more prone to issues. We can also look into the specific issues reported in the description column to identify any recurring problems.

Let’s start by summarizing the data to identify the most common deficiencies, the frequency of reports over the past two months, and any patterns related to locations, companies, or assets. ​​

❗️Error analyzing
It seems there was an error in my attempt to analyze the data, specifically related to a ‘date_reported’ column that does not exist in the dataset as I initially thought. Let’s correct this by first reviewing the available columns to identify the correct one for analyzing the timeline of reported deficiencies. Then, we’ll proceed with the analysis based on the correct column names and data structure. Let’s quickly list all column names to ensure we use the correct one for time-based analysis and other trend identifications. ​​

After reviewing the column names in the dataset, it appears that the correct column for analyzing the timeline of reported deficiencies might be last_reported_on rather than a non-existent date_reported. I will use this column to perform a time-based analysis, along with analyzing the most common deficiencies by asset and common locations where deficiencies have been reported. Let’s proceed with this adjusted approach. ​​

Based on the analysis of the data provided, here are some key findings and trends identified from the past two months:

Deficiencies Timeline:

Most Common Deficiencies by Asset:
The most commonly reported deficiency involves the “Location – Building”, with 160 instances. This suggests a broad range of issues not specific to a single type of equipment but potentially indicative of widespread or recurring building-related issues.
Specific assets like chillers, rooftop units, and boilers have also been frequently reported for deficiencies, but far less frequently compared to location-based reports. Notably, certain chillers and rooftop units have been reported 2 to 3 times.

Most Common Locations with Deficiencies:
Denton County Public Facilities and Dave & Buster’s locations (among others) have seen a higher frequency of reports, with up to 14 and 10 reports respectively. This could indicate specific sites that may require closer attention or proactive maintenance efforts.

Predictive Repair Planning:
Given these insights, your repair planning for the next quarter might focus on:

Increasing inspections or preventive maintenance at sites with high deficiency reports to catch and address issues early.
Paying special attention to building-related concerns and ensuring that routine checks are in place to prevent common deficiencies.

Considering a targeted approach for assets that have been repeatedly reported for deficiencies, such as specific chillers and rooftop units, to understand if there are underlying issues that need more comprehensive solutions.

By focusing on these areas, you can potentially reduce the incidence of future deficiencies and improve overall customer satisfaction through proactive service management.

February AI Prompt of the Month: How Many Man Hours Will I Need This Year?

I would bet that you often find yourself in a situation where you wish that you could just run a “quick report” of some business metrics. Assuming you have access to the data, usually it doesn’t take long to realize that reports can be pretty complicated to create. The data analysts (if you have any) probably rolled their eyes when you said the word “quick.” Luckily, AI can do hard things well, and fast! This prompt is just an example of turning a simple ServiceTrade export into a quick report, with a visualization, faster than even an Excel expert could combine a pivot table and a chart together (I know, because I took the data in this example and ran it through Excel using a pivot table and a chart, just to be *sure* the AI wasn’t lying to me).

The Prompt

Given the attached spreadsheet of recurring services that my company provides to my customers, can you create a forecasting visualization of man hours required to complete the services for the next 12 months? Base the date on the “due_next” field and the man hour estimate on the  “estimated_duration” field in the data.

The Output

The spreadsheet contains a wide range of columns (140 in total), including the fields id, ref_number, company, company_street, company_city, company_state, company_postalcode, store_number, location_name, and many more, with some fields relevant to your request such as estimated_duration. However, the due_next field you mentioned for basing the forecast on does not appear in the first few columns displayed. I’ll need to locate this field and the estimated_duration field specifically to proceed with creating the forecasting visualization.

Let’s identify and extract the necessary data for the due_next and estimated_duration fields from the dataset.

[AI stops and thinks for a bit here…]

The due_next and estimated_duration fields are indeed present in the dataset. Now, I’ll proceed to filter and prepare the data for the forecasting visualization. This will involve:

  1. Extracting only the relevant fields: due_next and estimated_duration.
  2. Ensuring that the due_next field is in a proper date format and that estimated_duration is in a numeric format.
  3. Aggregating the data by month to calculate the total estimated man hours required for each month in the next 12 months.

Let’s start with these steps.

[AI stops and thinks for a bit here…]

The data has been successfully filtered and prepared, focusing on valid entries for due_next and estimated_duration. However, it appears that the due_next dates include past years, which won’t be relevant for forecasting the next 12 months from the current date. I will adjust the dataset to include only future dates relative to the current date, and then proceed to aggregate and forecast man hours required for the next 12 months. Let’s correct this and prepare the forecasting visualization.

Now, let’s create a forecasting visualization for the man hours required to complete the services for the next 12 months, based on this aggregated data.

[AI stops and thinks for a bit here…]

Data chart showing man hours needed over time

The forecasting visualization illustrates the estimated man hours required to complete the services for the next 12 months, based on the new dataset. This forecast highlights the total estimated man hours for each month within the specified period, enabling effective planning and resource allocation for anticipated workloads.

January AI Prompt of the Month: Give me a recurring maintenance schedule with required parts

You probably have conversations with your technicians all the time about equipment at your customer’s sites, but have you ever considered having a conversation directly with the equipment instead? While we aren’t quite there yet (but we are working on it!) you can have the next best thing, by having a conversation with the manufacturer’s manual for a piece of equipment.

AI can take pretty large documents as context for your questions, simply by uploading the PDF to ChatGPT and then starting your chat. Here’s an example, using a 126-page Dunkirk boiler manual as context.

The AI Prompt

Give me a recurring maintenance schedule with required parts based on the manufacturer’s recommendations in the attached manual for a Dunkirk DCC-205 boiler.

The Output from ChatGPT

The Dunkirk DCC-205 boiler manual provides a detailed maintenance schedule, which should be performed by a qualified service technician. Here’s a summary of the recurring maintenance tasks and required parts:

Yearly Maintenance Schedule
1. Piping

  • Check boiler and system piping for leakage and ensure pipes are properly supported.

2. Vent

  • Check condition of all vent pipes and joints.
  • Verify vent piping terminations are free of obstructions and blockages.

3. Safety Relief Valve

  • Follow the valve manufacturer’s instructions for maintenance and repair.
  • Verify discharge pipe installation as per the Installation and Operation Manual (IOM).

4. System

  • Perform a full visual inspection of all system components.
  • Test all functions of the system (heating and safety).
  • Verify safe settings on boiler or anti-scald valve.
  • Verify programmed temperature settings.

5. Electrical

  • Check wire connections and ensure they are tight.
  • Verify smoke and CO detectors are installed and working properly, changing batteries if necessary.
  • Check that the circuit breaker is clearly labeled and operates correctly.

6. Chamber/Burner

  • Check burner and combustion chamber; clean as directed in the IOM.
  • Replace gaskets when checking the combustion chamber.
  • Clean the spark electrode and set the gap according to IOM directions.
  • Clean the flame sensor.

7. Neutralizer

  • Check and replace the condensate neutralizer if necessary.

8. Condensate

  • Clean the condensate pipe/trap and ensure proper flow and connection.

9. Pressure/Gas

  • Measure incoming gas pressure as per IOM.
  • Check gas piping for leaks and signs of aging.
  • Ensure all pipes are properly supported.

10. Combustion

  • Check CO and CO₂ levels in exhaust as per the Start-up Procedures.
  • Verify the continuity of all sensors and replace if corroded.

Required Parts

  • Gaskets for the combustion chamber.
  • Replacement parts for any detected leaks or damages in piping, vent, or electrical systems.
  • New batteries for smoke and CO detectors, if necessary.
  • Condensate neutralizer replacement, if required.

Important Notes

  • Continue inspections beyond the 4th year; maintenance should continue annually for the life of the boiler to ensure safe, worry-free operation.
  • All maintenance should be documented with the date of completion.

This schedule is based on typical maintenance requirements and should be adjusted based on the boiler’s operating conditions and environment. For specific part numbers and more detailed procedures, refer to the Dunkirk DCC-205 boiler manual.

First Follow-up Prompt: Create a Technician Task List

“Create a task list for my technician to perform this required work, breaking it up into separate lists by service frequency if needed (for example: Annual Service, Quarterly Service, etc…). The tasks should be as brief as possible and presented in bullet-point format.”

First follow-up Prompt: Technician Task List Output

Annual Service Tasks

  1. Piping
    • Inspect boiler and system piping for leaks.
    • Check pipe supports for integrity.
  2. Vent
    • Inspect vent pipes and joints.
    • Ensure vent terminations are unobstructed.
  3. Safety Relief Valve
    • Perform maintenance as per manufacturer’s instructions.
    • Check discharge pipe installation.
  4. System Inspection
    • Conduct a visual inspection of all system components.
    • Test heating and safety functions.
    • Verify boiler/anti-scald valve settings.
    • Check programmed temperature settings.
  5. Electrical
    • Tighten wire connections.
    • Test smoke and CO detectors; replace batteries if needed.
    • Check circuit breaker labeling and function.
  6. Chamber/Burner
    • Inspect and clean burner and combustion chamber.
    • Replace combustion chamber gaskets.
    • Clean and adjust spark electrode.
    • Clean flame sensor.
  7. Neutralizer
    • Inspect and replace condensate neutralizer if needed.
  8. Condensate
    • Clean condensate pipe/trap; ensure proper flow.
  9. Pressure/Gas
    • Measure incoming gas pressure.
    • Inspect gas piping for leaks and aging.
    • Check pipe support.
  10. Combustion Analysis
    • Measure CO and CO₂ levels in exhaust.
    • Check and replace sensors if corroded.

Quarterly Service Tasks
For the Dunkirk DCC-205 boiler, the manual does not specifically mention quarterly tasks. However, it’s a good practice to perform a brief visual inspection and check for any obvious issues or irregularities with the system on a quarterly basis.

As Needed
Immediate Response. Address any leaks, unusual noises, or operational issues as soon as they are noticed.

Second Follow-Up Prompt: Create a Proposal Summary

Take the information above and generate a summary that would be presentable as a proposal to a building facility manager to help us win a bid for performing this work on a recurring contract basis.

Second Follow-Up Prompt: Create a Proposal Summary Output

Proposal for Recurring Maintenance Services for Dunkirk DCC-205 Boiler

Introduction
We are pleased to submit our proposal for the recurring maintenance of your Dunkirk DCC-205 boiler. Our team of certified technicians is committed to delivering top-notch service, ensuring the longevity and efficiency of your boiler system.

Scope of Services
Our comprehensive maintenance program is designed to meet and exceed the manufacturer’s recommendations for the Dunkirk DCC-205 boiler. Our service includes:

  • Annual Service:
    1. Thorough inspection and maintenance of piping, venting, and electrical systems.
    2. Checking and adjusting the safety relief valve as per manufacturer’s guidelines.
    3. Complete system inspection including testing of heating and safety functions, and verifying valve and temperature settings.
    4. Chamber and burner inspection, cleaning, and necessary adjustments.
    5. Neutralizer and condensate system maintenance.
    6. Pressure and gas system checks, including leak detection and pipe support inspection.
    7. Combustion analysis to ensure optimal efficiency and safety.
  • Quarterly Service:
    • Regular visual inspections to identify and address any potential issues early.
  • As Needed:
    • Immediate response to any emergent issues, ensuring minimal downtime and disruption.

Benefits

  • Expertise: Our technicians are extensively trained and experienced in the specific needs of the Dunkirk DCC-205 boiler.
  • Safety and Efficiency: Regular maintenance ensures the safe and efficient operation of your boiler, reducing the risk of costly breakdowns.
  • Compliance: We adhere strictly to the manufacturer’s guidelines, ensuring that your system remains within warranty specifications.
  • Documentation: Detailed service logs are maintained for every visit, providing clear records for your facility’s maintenance history.

Commitment to Quality
We pride ourselves on delivering quality service with minimal disruption to your operations. Our team is equipped with the latest tools and technology to provide efficient and thorough service.

Conclusion
Our proposal represents not just a maintenance service, but a partnership to ensure the longevity and reliability of your Dunkirk DCC-205 boiler. We look forward to the opportunity to serve your facility and are confident that our dedication to quality and efficiency will contribute significantly to the smooth operation of your heating system.We welcome any questions or further discussions about how we can meet your facility’s specific needs. Thank you for considering our proposal.

How many years of expertise and hours of a seller’s time did we just skip by using documentation supplied by the manufacturer to begin a scope of work for this piece of equipment? When you consider the scale of commercial and industrial facilities, the time savings from using AI becomes pretty clear.

What do you think? We’d love to hear from you in the comments.

December AI Prompt of the Month: Design a Program to Capture More Deficiencies

The absolute best use of AI is to add more power to your workforce without having to hire a bunch of specialized employees. Can you imagine if you had a service manager on your staff that had an MBA? An Operations Manager with a Six Sigma Black Belt that could write comprehensive action plans? Turns out, this is a perfect job for ChatGPT! Check out this prompt to create a technician incentive plan:

The AI Prompt

I work for a commercial service contracting company that employs field technicians. My technicians use a software program that allows them to report deficiencies (problems with equipment) in the field, replete with descriptions, photos, and recommended solutions. I want to encourage my technicians to report more deficiencies. Can you please help me design an incentive program to encourage this desired behavior?

The Output from ChatGPT

Designing an incentive program to encourage your technicians to report more deficiencies can be highly effective. Here’s a structured approach to creating this program:

1. Set Clear Goals

  • Objective: Increase the number of reported deficiencies.
  • Metrics: Track the number of reports submitted per technician, quality of reports (detail in descriptions, clarity of photos), and usefulness of recommended solutions.

2. Understand Your Technicians’ Motivations

  • Conduct surveys or informal discussions to understand what motivates your technicians (monetary rewards, recognition, professional development, etc.).

3. Design the Incentive Structure

  • Monetary Incentives: Bonuses or gift cards for reaching certain thresholds of reports or for “report of the month.”
  • Recognition-Based Incentives: Public acknowledgment in company meetings, newsletters, or a “technician of the month” award.
  • Professional Development: Opportunities for training or advancement tied to their engagement and quality of reporting.

4. Ensure Fairness and Accessibility

  • Make sure the program is fair and does not inadvertently favor certain individuals or teams.
  • Provide necessary resources (like training on how to write effective reports or better access to reporting tools).

5. Communicate the Program Effectively

  • Clearly explain how the program works, the benefits, and how technicians can participate.
  • Use multiple channels for communication: meetings, emails, posters in common areas, etc.

6. Implement and Monitor

  • Launch the program and closely monitor its progress.
  • Keep track of participation rates and the quality of the reports.

7. Gather Feedback and Iterate

  • Regularly ask for feedback from technicians about the program.
  • Be ready to make adjustments based on what’s working and what’s not.

8. Celebrate Successes

  • Share success stories and acknowledge the contributions of technicians in improving the reporting process.

9. Ensure Long-term Engagement

  • Regularly refresh the program with new incentives or recognition methods to maintain interest.

10. Legal and Ethical Compliance

  • Make sure the program complies with all relevant laws and company policies.

Implementing such a program requires a balance between motivating technicians and maintaining the quality of the reports. Regular feedback and adjustment will be key to its success.

What’s next?

Not bad, huh? It’s certainly a lot better than starting from scratch or launching a project to hire an Operations Manager with a Six Sigma Black Belt. From here, you could ask ChatGPT to help with each step of the implementation, like writing out the policy, summarizing the responses you get from a survey, and more.

Have you considered using AI for help with ideas like this? What new ideas does this give you for how to use AI?  How would you change the prompt?  Tell us in the comments — we’d love to hear from you.

ServiceTrade Launches Smart AI to Help Contractors Maximize Efficiency and Deliver Exceptional Customer Service

New Smart AI integrates into the ServiceTrade platform so customers can leverage rich equipment history on over 10M commercial buildings to better complete work, recommend customer equipment improvements

ServiceTrade, a leading software platform for commercial contractors, today announced the launch of ServiceTrade Smart AI.  This new cutting-edge solution, powered by artificial intelligence, is directly integrated into the ServiceTrade Platform. With over a decade of experience in the trades, ServiceTrade is in an unparalleled position to empower contractors.

Contractors face many challenges in today’s competitive landscape. Finding the right technician for each job, maximizing limited labor resources, and providing top-notch customer service are crucial but difficult tasks.  Making things even more difficult, critical insights that technicians need are typically spread across multiple systems or, even worse, buried in systems built on cost measurement or project management rather than focused on customer equipment performance. 

ServiceTrade Smart AI addresses these challenges through advanced AI capabilities directly integrated into the ServiceTrade platform.  It aims to help contractors tackle their biggest challenges through optimized scheduling, predictive insights, and automated reporting.

Key features include:

“Technology is more important than ever for contractors to run an efficient operation and deliver exceptional customer service,” said Billy Marshall, CEO of ServiceTrade. “Smart AI takes our platform to the next level, using AI to boost operational outcomes, maximize labor productivity, and ensure customers receive the best possible experience.”

ServiceTrade Smart AI will be rolling out in phases over the coming months.  For a preview of Smart AI

To learn more about ServiceTrade Smart AI, please visit www.servicetrade.com/ai.  

AI wrote portions of this press release.