I want to give you some ideas on how you can automate your business, but also how to think about automation. Also, I want to show how an AI-first approach to consulting–like the one that Thunder employs–saves our customers time, money, and frustration.

We intend on continuing to add to the above and have a number of concrete plans we’re executing even now.

Let me tell you a little more about some of these things.

Estimator

We talk to a lot of companies about their challenges and their thoughts about how those challenges can be mitigated. When we get to a certain point, the goal is for them to hear about what we have imagined. As part of that, prospects obviously need to know what we think that solution will cost. To this end, we’ve worked hard to hone our estimation methodology and tools. 

Our main tool doesn’t have a fancy name. We just call it the Estimator. Fancy name or not, it does some fancy things. There are at least 5 different automations baked directly into the Estimator.

We can pull and push information between the Estimator and a Salesforce opportunity. Not only can this be done on demand, we automatically synchronize open opportunities with their estimators. This makes sure that we have details like the amount, cost, hours, and more within Salesforce that reflects any changes that have been made to an estimate. 

We can generate portions of our proposal from the Estimator. The proposal is a presentation that walks our prospects through the solution, including the scope, methodology, timeline, and price. Not only does this allow us to build proposals faster, it also makes sure that the proposal matches the estimate perfectly. We can also generate portions of our contract. Once again, this helps us decrease the amount of time we spend writing contracts and get them into our customers’ hands more quickly. It also ensures that our contract matches the estimate.

We also use our estimator to generate the resource assignments for projects so that our project plan matches exactly with our estimate. Once the project is created, our team can also pull all of the requirements as written in the Estimator. A little later, you can see how requirements lay the foundation for our User Story Assistant to help generate user stories.

Thunder Platform + Checklist

There are simply too many automations to list around our Thunder Platform. This is the tool we use to track an engagement including all of the requirements, user stories, test cases, issues, risks, resources, time spent, budget, and more. We have baked in automations to help us manage budgets, create bills, import tasks, track budgets, and so much more. Our goal is to have the platform not be a “tracking system” but an interactive part of managing an engagement, helping everyone do their job better and keeping accountability clear.

The system provides our team with a common approach to managing requirements, user stories, and sprints. We use tools to build out Gantt charts and to do user story maintenance and sprint planning.

One major part of the Thunder Platform are the project tasks. When we re-built our methodology, we took into consideration what each of us have learned from managing engagements in our careers. We learned from the methodologies we’d used. We discussed the challenges we had encountered. We kept what worked. We ideated on how to sidestep challenges. We came up with a list of  things that to do on every project in order to give it the highest possible chance of success. That list is now 85 tasks that we put on our checklist for project success. That checklist lives right in the Thunder Platform and each task is assigned to the appropriate member of the team. They have due dates that make sense to the project timeline and are tracked to completion.

Thunder Early Warning System

A Thunder exclusive, this is our fully automated scoring and suggestion system for our engagements. Every day, every active engagement is run through a set of 25+ diagnostics to determine whether there’s anything that might cause an issue in the future. Are tasks finishing late? Are our assignments overallocated? Is there anything we can do to improve the quality of our documentation? The Early Warning System checks all of these things and generates a score that tells us the chance of “storms”. It offers the team suggestions on how to improve. This doesn’t take over for our engagement oversight, but it helps them to know where to look on any given day.

The Early Warning System helps to remove a lot of the surprises we used to experience on engagements. It is no replacement for excellent oversight staff, like project and engagement managers. It does, however, allow them to spend less time combing through all of the information that makes up a project and pinpoint quickly where to invest their energy.

Thunder User Story Assistant

User stories describe a feature from an end-user perspective and are crucial for projects as they ensure the software being built meets the actual needs and expectations of the users. Because of their importance, we’ve worked to make sure we get them just right. Our User Story Assistant uses AI to help suggest, enhance, and grade user stories for us. It helps point us to places where we can add a missing detail, have not followed best practices, or where we might not have fleshed out the story well enough. It also helps us to do the same with test cases–providing suggestions and grades. This works together with the Early Warning System, which will notify us if we’ve marked a user story for a build with a low grade.

For our customers, this means a higher quality end product at a lower cost. When a user story is passed to you for approval, it should be of very high quality. When our team provides testing, you can expect test cases to be provided covering the majority of the build.

We are continuing to invest in this functionality, adding context so that the stories will only get better.

Thunder Customer Portal

Everything above is what we’re doing behind the scenes to make an engagement a success. To be great partners to our customers, it isn’t enough to just do the right things–we needed to show you. So we provide our customers with a portal that allows them to follow along at home with their engagement. Thunder customers can see their budget, timeline, issues, risks, requirements, user stories, project team, and any files associated with the project. They can approve or reject user stories. They can log an issue at any time.

If, at any point in the engagement they feel like things aren’t going right, they can escalate the engagement directly from the portal. When this happens, it alerts our management team to begin a process that includes working directly with our customers to plan how the engagement can get back on track.

So Much More

There is so much more I want to describe. We have automated and gamified doing the right thing at Thunder–providing achievements we celebrate for learning, hitting milestones, or winning awards. Data moves between several systems to make sure we have the latest information about bills, time off, and more.

Like anyone in business today, our team uses some off-the-shelf AI tools like Google Gemini or tools baked into applications like Lucid Chart to accelerate our work. Our team is eager to share tips and tricks with each other like how to use Google Gemini to help manage your email inbox or calendar. Google Gemini meeting notes have become a standard for helping to understand meetings. We continue to explore which of the tasks our team is doing regularly are something we should institutionalize, so we encourage responsible experimentation.

Automate All the Things

Automation hits at every point in our process. Now that you know about some of our tools, take a look at the intersection of each tool and an engagement. Note that this is just a sampling of what is happening.

1. We create an Estimator using our built-in library of tasks. We generate the proposal and the contract.
2. We create resource requests from the Estimator. They match the budget and timeline we shared with the customer in the proposal and contract exactly. Our system helps us match the resource based on skills and availability–so we have earmarked the right people for your engagement even before you sign.
3. Negotiation happens and the customer ultimately makes the right decision and chooses to sign a contract with Thunder. Messages are sent to our internal Slack channels celebrating and so people can start planning.
4. A Project record is created directly from the Opportunity. Information is carried over to the Project to maintain accuracy.
5. All the tasks that make up our process are imported with due dates & owners assigned automatically based on the project start date.
6. Project tasks are monitored for on-time completion by the Early Warning System
7. The Estimator creates Requirement records in Thunder Platform with a source of “Initial Contract”, new requirements will have a different source (e.g., Discovery). This allows us to keep track of when requirements were found, put into backlog, etc. Ultimately, it makes sure we’re meeting every contractual requirement.
8. User Stories are created related to each requirement. Some will come from a large library we maintain. We have a library of over 800 user stories that are related to the requirements we use often in estimates, the system “finds” them automatically and adds them to the project with a few clicks. The Early Warning System makes sure that every Requirement has at least one User Story.
9. Some user stories for new requirements will be generated via AI. Some will be written by one of our business analysts and enhanced via AI.
10. Every user story is graded whenever it is changed (A-F) based on user story best practices and thoroughness.
11. The customer will be prompted in the customer portal to review and approve their user stories, they have the ability to provide any feedback via chatter to clarify or suggest improvements.
12. Generative AI can create a solution design narrative based on the written user stories, summarizing the overall approach.
13. ZapExchange accelerators provide hundreds or thousands of hours of IP for little cost to the customer, decreasing costs and de-risking projects.
14. AI Code Generation provides a cost savings and uses documented best practices
15. Test Cases can be generated via AI based on the user story (especially the acceptance criteria). As with all the rest of the project data, test cases are visible to the client in the portal
16. We track every Test Case Execution showing the expected and actual results proving what we’ve tested and when
17. Our team has an integrated Thunder-built tool that allows us deeper insights in the budget and ways to do some scenario modeling
18. We manage issues and risks within Thunder PSA, and these are shared with the client allowing collaboration (Chatter)
19. Project Escalations are tracked like cases in Thunder PSA keeping track of who owns it, what the plan is, and current progress.
20. A customer can escalate from the portal at any time to tell us that they have concerns and we will track it and manage it as a team

This is what I do every day. I’m working to find more ways for us to become more efficient and provide better experiences for our staff and customers. We have a lot more ideas–some that are already in progress, some that we’re ideating on, and some that we don’t even yet know how to make happen. 

Furthermore, this is what Thunder does. Our clients come to us to understand how to increase their customer service efficiency, provide more accurate quotes in less time, provide marketing automation that increases revenue, and more. They want to use the tools provided by Salesforce to maximize the investment they’ve made there. They want to use generative and predictive AI to add efficiency. They want agents to take over tasks within their businesses. That’s what we do–for ourselves and for our clients. Doing these things for ourselves helps us to do more for our clients at a lower cost. Isn’t that the kind of system integrator with which you should be working?