Operations Efficiency
Streamline your operations and create a centralized single source of truth for enhanced efficiency.
We're in the early alpha stage, this page is constantly evolving, book a call with us to learn more.
Context
Streamline your operations and improve efficiency with our Operations Efficiency solution. By centralizing data and processes, you can create a single source of truth, enabling better collaboration and reducing manual errors. Automate repetitive tasks and leverage advanced analytics to gain insights and make data-driven decisions for continuous improvement.
Benefits
Follow Your Company Metrics
Monitor and visualize key company activities, providing a centralized overview of your organization’s performance.
Automate Processes
Streamline and automate data workflows to eliminate manual tasks and ensure data consistency across your organization.
AI-Powered Task Prioritization and Optimization
Receive AI-driven recommendations for optimizing operations, helping your team focus on high-impact tasks and projects.
Features
Connect to any third-party tool
With Naas Python capabilities and templates, you have the flexibility to connect to any third-party tool and access the important data of your business. Whether it's CRM systems, marketing platforms, or data analytics tools, integrate and retrieve data from these sources to get a comprehensive view of your business operations and make informed decisions based on real-time, up-to-date information.
Apply your own business rules
The use of Python and notebook templates in the engine also allows users to easily create and apply their own business rules. With Python's flexibility, users can define custom rules that align with their specific needs. Notebook templates provide a structured environment for documenting, sharing, and deploying these rules, enabling efficient collaboration and streamlined decision-making processes.
Chat with Your Operation Agent
Engage in real-time conversations with your dedicated operational agent to address any queries or concerns based on the data collected from your different systems.
Receive Automated Email Reports
Stay updated on key metrics and insights with automated email reports delivered directly to your inbox.
Send Product Signals on Slack
Seamlessly push important product signals and updates with your team on Slack for enhanced collaboration and visibility
Data Model
PERFORMANCE_TRACKING
Dataset
| DATE | DEPARTMENT | ACTIVITY | OUTPUT | KEY METRIC | METRIC VALUE |
|---|---|---|---|---|---|
| 2023-05-24 | Sales | Closed Deals | 10 deals | Revenue | $20,000 |
| 2023-05-24 | Marketing | Campaigns Launched | 3 campaigns | Leads Generated | 200 |
| 2023-05-24 | HR | Interviews Conducted | 5 interviews | Positions Filled | 2 |
| 2023-05-24 | Production | Units Produced | 1000 units | Efficiency | 95% |
Schema
{
"type": "object",
"properties": {
"DATE": {
"type": "string",
"format": "date",
"description": "The date of the activity."
},
"DEPARTMENT": {
"type": "string",
"description": "The department that performed the activity."
},
"ACTIVITY": {
"type": "string",
"description": "The activity that was performed."
},
"OUTPUT": {
"type": "string",
"description": "The output of the activity."
},
"KEY METRIC": {
"type": "string",
"description": "The key metric used to measure the performance of the activity."
},
"METRIC VALUE": {
"type": "string",
"description": "The value of the key metric."
}
},
"required": ["DATE", "DEPARTMENT", "ACTIVITY", "OUTPUT", "KEY METRIC", "METRIC VALUE"]
}
DATA_INTEGRATION
Streamline and automate data workflows to eliminate manual tasks and ensure data consistency across your organization.
Dataset
| EVENT ID | EVENT TIMESTAMP | DATA SOURCE | EVENT TYPE | TASK ID | TASK NAME | TASK STATUS | USER ID |
|---|---|---|---|---|---|---|---|
| 1 | 2023-05-24 10:00:00 | Trello | Task Update | T1001 | Develop feature X | Completed | U001 |
| 2 | 2023-05-24 11:00:00 | HubSpot | Task Creation | H2001 | Contact lead Y | Pending | U002 |
| 3 | 2023-05-24 12:00:00 | Notion | Task Deletion | N3001 | Meeting with Z | Deleted | U003 |
| 4 | 2023-05-24 13:00:00 | GitHub | Task Update | G4001 | Fix bug A | In Progress | U004 |
| 5 | 2023-05-24 14:00:00 | Harvest | Task Creation | Hr5001 | Invoice client B | Pending | U005 |
| 6 | 2023-05-24 15:00:00 | Clockify | Task Update | C6001 | Time tracking C | Completed | U006 |
Schema
{
"type": "object",
"properties": {
"EVENT ID": {
"type": "integer",
"description": "A unique identifier for the event."
},
"EVENT TIMESTAMP": {
"type": "string",
"format": "date-time",
"description": "The time the event occurred."
},
"DATA SOURCE": {
"type": "string",
"description": "The source of the event data."
},
"EVENT TYPE": {
"type": "string",
"description": "The type of event."
},
"TASK ID": {
"type": "string",
"description": "The ID of the task involved in the event."
},
"TASK NAME": {
"type": "string",
"description": "The name of the task involved in the event."
},
"TASK STATUS": {
"type": "string",
"description": "The status of the task at the time of the event."
},
"USER ID": {
"type": "string",
"description": "The ID of the user who triggered the event."
}
},
"required": ["EVENT ID", "EVENT TIMESTAMP", "DATA SOURCE", "EVENT TYPE", "TASK ID", "TASK NAME", "TASK STATUS", "USER ID"]
}
AI-Powered Task Prioritization and Optimizations
Dataset
This AI-Powered Task Prioritization and Optimization solution provides AI-driven recommendations for optimizing operations. Here's an example of what the dataset might look like:
| TASK ID | TASK NAME | USER ID | PROJECT ID | ESTIMATED COMPLETION TIME | PRIORITY SCORE | OPTIMIZED ORDER |
|---|---|---|---|---|---|---|
| T1001 | Develop feature X | U001 | P001 | 5 hours | 0.8 | 1 |
| H2001 | Contact lead Y | U002 | P002 | 2 hours | 0.6 | 3 |
| N3001 | Create marketing plan | U003 | P003 | 10 hours | 0.9 | 2 |
| G4001 | Fix bug A | U004 | P004 | 3 hours | 0.7 | 4 |
Schema
The data contract or schema might look something like this:
{
"type": "object",
"properties": {
"TASK ID": {
"type": "string",
"description": "The ID of the task."
},
"TASK NAME": {
"type": "string",
"description": "The name of the task."
},
"USER ID": {
"type": "string",
"description": "The ID of the user assigned to the task."
},
"PROJECT ID": {
"type": "string",
"description": "The ID of the project the task is associated with."
},
"ESTIMATED COMPLETION TIME": {
"type": "string",
"description": "The estimated time to complete the task."
},
"PRIORITY SCORE": {
"type": "number",
"description": "The AI-generated priority score of the task."
},
"OPTIMIZED ORDER": {
"type": "integer",
"description": "The AI-generated order in which tasks should be completed."
}
},
"required": ["TASK ID", "TASK NAME", "USER ID", "PROJECT ID", "ESTIMATED COMPLETION TIME", "PRIORITY SCORE", "OPTIMIZED ORDER"]
}
How to Contribute?
Collaborate with Us on our Public GitHub Repo
Accelerate development by working with us on issues in our public GitHub repository: https://github.com/jupyter-naas/engine-operations.
Submit Your Ideas and Improvements
Create GitHub Issues or Participate in GitHub discussions with fellow community members. Your ideas and suggestions for improvements are always welcome.
Talk About Naas On Social Media
If you like what we are doing, share your story and case studies on social platforms to inspire others in the community. Your experiences can provide valuable insights for others.