AI Analysis of LinkedIn® Profile "Experience" Content

The Experience section of a LinkedIn® profile is the place to showcase your professional work history and highlight key responsibilities, achievements, and skills gained from past and current roles. It's a critical part of the profile, allowing potential employers, colleagues, and professional contacts to understand the user’s background, expertise, and career progression. It’s also critical for another reason … it’s the section of a profile that you need to make data-rich for data mining by LinkedIn®-specific search tools.

Each professional experience defined has a sub-section labeled Description. It’s here, within a boundary of 2,000 characters, you can document your Role and Responsibilities, Technical Expertise, Business Impacts, Problem-Solving & Analytical Skills, and Results.

Now, you may feel you’ve done an adequate job filling this out, but is that so? How would an AI-tool used in a talent search assess your work? Would it put you at the top or the bottom of a list of potential talent in the marketplace?

ChatGPT is an advanced AI-language model created by OpenAI that can understand and generate human-like text. Think of it as a virtual assistant that can answer questions, help with writing, generate ideas, and provide information on a wide range of topics. It's like having a smart conversational partner that can assist with anything from brainstorming to language translation.

ChatGPT has evolved since its initial release in 2018 as a smaller language model (GPT-1). Over the years, OpenAI has released improved versions (GPT-2, GPT-3, GPT-4). OpenAI has trained each model on larger and more complex datasets. This improved its ability to understand subtle differences in language, which improved its response accuracy.

The most recent model, GPT-4, is much more sophisticated. It can handle complex tasks better, remember parts of the conversation, and provide more accurate answers. With advancements in understanding context, GPT-4 can now engage in extended, meaningful conversations and adapt its responses to a variety of tones and topics. Here are its key features:

Multifunctional Tool: GPT-4 can assist with an array of tasks: writing, summarizing, coding, brainstorming ideas, or even explaining complex concepts.

Personalization: The model can follow specific instructions and adjust its tone and detail level, offering responses tailored to personal or professional needs.

Image and Web Features (for specific versions): GPT-4 has integrated visual capabilities, can analyze images, describe them, or answer questions about them. It can even browse the internet for real-time information if allowed.

I’ve been working with ChatGPT Plus (the paid version) for quite some time now, performing research and literary simulation. It has proven to be an invaluable tooI. It’s become quite obvious that GPT-4 should be capable of performing a content assessment.

With this in mind, I conducted an experiment. I have a strong profile. I used GPT-4 to analyze one of my description entries. I then picked a profile at random that had what I would assess as a weak description entry and tested it. What follows are the results.

AI Analysis Experiment (I have done no grammatical corrections. It stands as written.)

I analyzed one of my professional experiences with the following question:

Does this content meet the following criteria of in-depth role and responsibility, technical expertise, business impact, problem-solving and analytical skills, and being results-oriented?:

Content:

I managed an IT development team supporting the implementation of SAP in Poughkeepsie, NY; Fujisawa, Japan; Dublin, Ireland; and Montpellier, France. Created and executed a software merge methodology, using IntelliCorp software and the Volere Requirements Engineering Methodology, for the Poughkeepsie and Fujisawa SAP instances, with no interruption to business processing for any manufacturing locations, and no major severity issues. I used the Volere Requirements Engineering Methodology. I performed Mind Mapping analyses with Mindjet’s MindManager application to develop and deliver a real-time QA application running across the IBM hardware manufacturing operations with no significant severity issues.

GPT-4 returned the following results:

Yes, this content meets the criteria very well, as it provides depth in each area:

1. In-Depth Role and Responsibility:

The description includes managing an IT development team for SAP implementations across multiple international locations (Poughkeepsie, Fujisawa, Dublin, and Montpellier), showcasing a substantial leadership role with a global scope. Specific responsibilities include creating and executing a software merge methodology and developing a real-time QA application, illustrating a hands-on approach and an in-depth involvement in both strategy and execution.

2. Technical Expertise:

Technical expertise is clearly demonstrated with the use of IntelliCorp software, the Volere Requirements Engineering Methodology, and Mindjet’s MindManager for mind mapping. These tools and methodologies show knowledge in requirements engineering, real-time application development, and structured planning, all of which are relevant and advanced technical skills in IT and SAP management.

3. Business Impact:

The content emphasizes that the software merge methodology was implemented with no interruption to business processing and no major severity issues. This shows that the impact on business operations was carefully managed and that the approach maintained continuity. Additionally, developing a real-time QA application for IBM hardware manufacturing supports operational efficiency and product quality, which are valuable contributions to the organization’s manufacturing success.

4. Problem-Solving and Analytical Skills:

The use of Mind Mapping with Mindjet’s MindManager for analysis and development of a QA application reflects a structured, analytical approach to problem-solving. Creating a software merge methodology for SAP instances suggests the ability to design solutions for complex integration challenges, showing strong analytical and problem-solving skills in ensuring seamless functionality across systems.

5. Results-Oriented:

The results-oriented nature is clear through the outcomes emphasized: no major severity issues and no interruptions to business processing, both of which indicate that the work was successful and minimized risks to operations. By detailing the practical results of the projects, such as a fully operational QA application and the smooth execution of the SAP merge, the content effectively highlights a focus on achieving measurable, impactful outcomes.

Conclusion

This content is well-rounded and covers each of the criteria in depth, making it highly suitable for a LinkedIn® profile or resume. It effectively showcases a leadership role, technical knowledge, business-oriented results, analytical thinking, and a commitment to delivering successful outcomes.

I chose an individual profile at random and used one of its Experience Description sub-sections and reran the analysis with the following results:

This content touches on the criteria but lacks depth in several areas. Here’s how it aligns with each criterion and recommendations for enhancement:

1. In-Depth Role and Responsibility:

The content describes tasks like data collection for inventory and quality control, developing policies for suppliers, and supporting shipping and logistics. These roles imply involvement in operational support but do not fully capture an in-depth or leadership role. To strengthen this, consider expanding on specific responsibilities, such as coordinating with teams, managing processes, or overseeing specific aspects of inventory or quality control.

2. Technical Expertise:

Collecting and collating data for inventory and quality control suggests some familiarity with inventory management and quality assurance processes. Developing policies for prospective suppliers implies some knowledge in supplier evaluation or procurement standards. Detailing specific tools, software, or methodologies used (e.g., inventory management systems, quality control standards, or logistics software) would highlight technical expertise more effectively.

3. Business Impact:

The current content provides limited information on business impact. However, supporting inventory and quality control and logistics indirectly affects efficiency and product quality. To enhance this, mention any measurable improvements, such as reduced inventory costs, improved supplier quality, or increased efficiency in shipping and logistics due to the support provided.

4. Problem-Solving and Analytical Skills:

The content does not provide details on problem-solving or analytical skills. However, collecting and collating data suggests some level of analysis for inventory and quality control. To strengthen this, describe specific issues resolved, such as identifying inventory discrepancies, improving supplier compliance, or enhancing shipping efficiency through analysis and problem-solving.

5. Results-Oriented:

The content lacks specific results, making it difficult to assess whether actions were outcome-focused. While policy development for suppliers is valuable, including the impact of those policies—like improved supplier quality or compliance rates—would better demonstrate a results-oriented approach. Adding examples of achieved outcomes, like reducing errors, meeting shipping deadlines, or improving inventory accuracy, would highlight a focus on results.

Areas for Enhancement

To make this content stronger:

- Expand on responsibilities and specify any tools or systems used to improve inventory, quality control, or logistics.

- Include metrics or outcomes to showcase business impact and results (e.g., reduced lead time, improved inventory accuracy, or enhanced supplier compliance).

- Describe challenges faced and problem-solving methods, such as improvements in logistics efficiency or quality control issues resolved through data analysis.

Conclusion

While this content provides a basic overview of responsibilities, it needs more detail to fully meet the criteria. Adding specifics around technical tools, outcomes, problem-solving examples, and business impact would make this description stronger and more compelling.

ChatGPT’s GPT-4 can analyze LinkedIn® profile content, providing valuable insights to help you strengthen your profile. You need to leverage this tool, or an AI-equivalent to make your profile more compelling and optimized before AI-driven assessment tools for talent discovery become the norm.

Image created with DALL·E 3 by JH Capron