Use ChatGPT to Write Annaul Performance Goals for 2023

Every January/February, millions of corporate employees are going through the annual performance goal setting. Could ChatGPT help us develop better goals and make the process smoother? Let's find out.

Oh, in case you haven't heard about ChatGPT, it is a public AI-model specialized in handling human language-related tasks in a conversational manner (aka “chat”). It was built by OpenAI.

Let's break up this experiment into two steps:

Create a list of objectives, tasks and developmental needs which may be considered as “raw materials”.
Convert the “raw materials” into shiny goal statements.

Step 1: Define objectives, tasks and developmental needs

In this step, I will let ChatGPT serve as a R&D manager whose job is to help researchers define objectives, prioritize tasks and identify development opportunities. Here is my first prompt that both sets up the stage and asks for some general advice.

I want you to act as a R&D manager of a group of PhD researchers. Your job is to help your direct reports develop their annual performance goals. This could involve defining key objectives, prioritizing/planning tasks and identifying development opportunities. My first request is "I need some tips on how to identify my key objectives for Project X, where my role is to develop an accelerated analytical method to quantify the color change of white pigment under extended storage. ".

Here are some tips for identifying key objectives for Project X: 1. Start by reviewing the project's overall goal and objectives. Understand what the project is trying to accomplish and what the end-result should be. 2. Consider what specific outcomes you need to achieve in order to contribute to the overall goal and objectives. These might include developing a new analytical method, improving the accuracy of existing methods, or identifying new applications for the method. 3. Identify any specific challenges or obstacles that you need to overcome in order to achieve your objectives. These might include technical obstacles or limitations in available resources. 4. Prioritize your objectives based on their level of importance and feasibility. Focus on the most important and achievable objectives first, and then work on the others as resources permit. 5. Clearly define your objectives in measurable terms, so that you can track your progress and know when you have achieved them. For example, your key objective for this project might be to "develop an accelerated analytical method with a quantifiable measurement of color change in white pigments under extended storage with an accuracy of at least 90% within a month." 6. Communicate the objectives with your team, your supervisor, and other stakeholders and get their feedback.

The suggestions are certainly quite reasonable as a starting point. So let's continue and ask for some specific ideas for inspiration.

My second request is "I need some ideas for key objectives".

Here are some examples of potential key objectives for Project X, given that the goal of the project is to develop an accelerated analytical method to quantify the color change of white pigments under extended storage: 1. Develop a new analytical method that can accurately measure the color change of white pigments in a fraction of the time currently required. 2. Increase the accuracy of the analytical method to at least 90% or higher. 3. Identify and test new applications for the analytical method, such as measuring the color change of other types of pigments or in different storage conditions. 4. Reduce the cost of the analytical method to make it more accessible to a wider range of users. 5. Develop software or an app to make it easy for users to conduct the analysis and interpret the results. 6. Develop a user manual and training materials for the method to help new users get started quickly 7. Publish the research in scientific journals or conference proceedings to disseminate the new method and attract potential collaborators or customers. 8. Collaborate with industrial partners to validate the method in real-world applications and bring it to the market.

The list of proposed objectives is quite comprehensive. I see that ChatGPT has tried to tackle the problem from many different angles. Some of the out-of-the-box ideas are especially appealing.

If I want ChatGPT to help develop some key deliverables based on an objective, this is what I can do:

My third request is "I need help on how to plan my quarterly deliverables for idea 1."

Sure, here are some steps you can take to plan your quarterly deliverables for collaborating with industrial partners to validate the method in real-world applications and bring it to the market: 1. Identify the specific industrial partners you want to work with. This could include companies in the pigments industry, or companies that use white pigments in their products. 2. Establish clear goals and expectations for the collaboration. This should include what you hope to accomplish through the collaboration, as well as what the industrial partner hopes to achieve. 3. Develop a timeline for the collaboration. Identify key milestones and deadlines that need to be met in order to bring the analytical method to market. 4. Identify the resources needed for the collaboration. This may include funding, laboratory space, equipment, or personnel. 5. Develop a budget for the collaboration. This should include projected costs for resources such as equipment, materials, and travel. 6. Develop a communication plan. Identify the key stakeholders that need to be kept informed of progress, and establish a schedule for reporting on the project's progress. 7. Develop a plan for protecting the intellectual property of the project. This should include identifying what needs to be protected, and developing strategies for protecting the IP. 8. Break down the project deliverables into manageable tasks and establish a schedule for completing each task. Assign responsibilities and due date for each task, and track progress to make sure everything is on track. 9. Identify possible risks and contingencies, and plan how to mitigate them. 10. Review and adjust the plan regularly, as the collaboration proceeds, to ensure that the project stays on track. Remember, to successfully collaborate with industrial partners, both the industry and the researchers should benefit. Be prepared to communicate the benefits of the collaboration to the industry, and keep an open mind on their feedback, as they might know the specific requirements and limitations of their products.

Again, very valuable suggestions at (almost) no cost!

Now, can I ask ChatGPT to modify my objectives, for example, to incorporate my developmental needs?

My fourth request is "I would like to learn more about data analytics and machine learning. How do I incorporate such aspects into my project".

Data analytics and machine learning can be powerful tools for enhancing the performance and capabilities of analytical methods like the one you're developing for Project X. Here are some ways you can incorporate data analytics and machine learning into your project: 1. Data pre-processing: In order to use machine learning algorithms, you need to have a dataset that's appropriate for training the model. This may involve cleaning and formatting the data, as well as selecting a subset of the data to use for training and testing. 2. Model selection: Once you have your data prepared, you can select and train a machine learning model. There are many different types of models to choose from, such as linear regression, decision trees, or neural networks. The choice of model will depend on the nature of the data and the problem you are trying to solve. 3. Model training: Once you have selected your model, you can train it using your dataset. This typically involves adjusting the model's parameters to optimize its performance on the training data. 4. Model evaluation: After training, you'll need to evaluate the model's performance on a separate test dataset to see how well it generalizes to new data. This will give you a sense of how accurate the model is, and help you identify any areas for improvement. 5. Model deployment: Once you have a trained model that performs well on the test dataset, you can use it to make predictions on new data. Depending on the complexity of the model and the type of data, this may involve writing code to implement the model, or using software libraries to make predictions. 6. Data analysis: Once the model is deployed, you can analyze the results of predictions, to check for any discrepancies or unexpected outcomes. This will help you to determine any shortcomings or inaccuracies of the model and make adjustments to it, if necessary. It's important to keep in mind that data analytics and machine learning are complex and rapidly-evolving fields, and incorporating these techniques into a research project may require a significant investment of time and resources. Additionally, not all analytical methods would benefit from these techniques, so you should consider the feasibility of applying these methods on your particular case.

Wow, these are certainly some very good ideas for me to consider. Thanks, ChatGPT!

At any time, if you have any questions or need clarification, you can continue with follow up questions before moving onto a different topic.

Step 2: Craft SMART performance goals

In the corporate world, SMART (Specific, Measurable, Achievable, Relevant, and Time-Bound) is perhaps the gold standard for goal language. Having defined our key deliverables, timelines and learning opportunities, the next step is phrase them in the SMART format so it works best for both you and your manager.

Unsurprisingly, the almighty ChatGPT already knows what SMART goal is:

What is SMART performance goal?

SMART is an acronym that stands for Specific, Measurable, Achievable, Relevant, and Time-bound. It is a framework for setting performance goals that helps to ensure that they are clear, concise, and actionable. A SMART performance goal will have the following characteristics: - Specific: Clearly defined and easy to understand. - Measurable: Quantifiable, so progress can be tracked and success can be evaluated. - Achievable: Realistic and attainable, given the available resources and constraints. - Relevant: Aligned with the organization's overall mission and strategy. - Time-bound: Has a deadline for completion. By setting SMART performance goals, organizations and individuals can improve the chances of achieving their objectives and reaching their desired outcomes.

Nevertheless, we can re-enforce this concept and tailor the output by providing some examples in our prompts. The example template used below is based on this Atlassian post: How to write SMART goals.

I want you to act as a R&D researcher. Your job is to write annual performance goals following the SMART principle. For example, "Achieve [quantifiable objective] by [timeframe or deadline]. [Key players or teams] will accomplish this goal by [what steps you'll take to achieve the goal]. Accomplishing this goal will [result or benefit].". My first request is to create a goal statement for "Develop a new analytical method that can accurately measure the color change of white pigments in a fraction of the time currently required." with the following parameters: - quantifiable objective: 50% shorter measurement time with at least 90% accuracy - deadline: June 30 - key players: my technician and I - steps: - literature research (Jan 1 - Jan 31) - design & prototyping (Feb 1 - April 30) - validation (May 1 - May 31) - deployment (June 1 - June 30) - benefits: - shorten sample measurement time by 50% - accelerate formulation development

Develop a new analytical method that can accurately measure the color change of white pigments in a fraction of the time currently required by June 30th. Me and my technician will accomplish this goal by conducting literature research from Jan 1st to Jan 31st, designing and prototyping from Feb 1st to April 30th, validating from May 1st to May 31st, and deploying the method from June 1st to June 30th. By achieving a 50% shorter measurement time with at least 90% accuracy, we will be able to shorten sample measurement time by 50% and accelerate formulation development.

Well, the goal produced by ChatGPT has followed the template, but perhaps too literally so it sounds rather mechanical. Let's ask ChatGPT to rephrase it.

Paraphrase the goal statement so it sounds less mechanical. Use bullet points for the steps to achieve the goal.

Develop a cutting-edge analytical method for measuring the color change of white pigments. The goal is to achieve a 50% reduction in measurement time with at least 90% accuracy by June 30th. The key players involved in this project are myself and my technician. To achieve this goal we will: - Conduct extensive literature research from January 1st to January 31st - Design and develop a prototype from February 1st to April 30th - Validate the method through thorough testing from May 1st to May 31st - Implement and deploy the method from June 1st to June 30th By successfully completing this project, we will be able to significantly shorten sample measurement time by 50% and accelerate formulation development process.

I think this sounds much better! Now I just need to repeat the process to create all my goals for 2023!

Disclaimer: I am not a prompt engineer and my prompts are definitely not optimized. Suggestions for improvement are more than welcome!