Keywords

1 Introduction

Product Operations (Product Ops) is an emerging function in software-developing organizations, designed to bolster software product management (SPM) by incorporating a distinct operational aspect. This function is defined as one that makes companies more efficient and allows them to scale without friction, and empowers product teams in four dimension [6]:

  1. 1.

    Ensuring that software product managers regularly receive clean and reliable data to base their decisions on (data management dimension);

  2. 2.

    Managing the tooling, processes, and infrastructure used by the product team, establishing and communicating best practices (tool and process management dimension);

  3. 3.

    Allowing software product managers to focus on core SPM work by reducing the administrative burden and acting as a pro-active assistant (operational complement dimension);

  4. 4.

    Fostering cross-departmental and cross-team communication, collaboration, and coordination, ensuring alignment and preventing silos (collaboration dimension).

Despite the growing recognition of the benefits associated with the emerging business function of Product Ops, there is no consensus on the role’s specific responsibilities and how the Product Ops role should be implemented [6, 7]. To address this, the paper evaluates job advertisements (job ads) for Product Ops positions to provide a coherent portrait of a Product Ops professional.

Rafaeli and Oliver [8] have argued that job ads are a relevant form of organizational communication and demonstrate the richness and complexity of information that can be shared via such ads. Most ads have a similar “skeleton”, consisting of four parts: the identity of the hiring organization, the human resources demands it needs to meet, the description of the requirements to fulfill these demands, and contact information for applicants. While this skeleton is sufficient to fill the employment need, most ads go further and include information regarding the legal requirements that the organization complies with, as well as the organization’s size, financial situation, history, expected future products, values, and culture [8]. The authors argues that job ads can also be aimed at the general public (including potential investors), current employees, and other organizations [8]. The objectivity of the ads must therefore be approached with caution, as a job ad reflects how an organization wishes to be perceived by these audiences. While job ad analysis alone may not provide a comprehensive description of the discipline in question, we believe that an analysis of the skills and requirements listed in the core “skeleton” of the ads provides a valuable vantage point nonetheless. In this assessment we are not alone, as skill identification from job ads has been gaining popularity in the academic community [4]. A recent survey identified as many as 108 research articles on the subject of skill identification from job ads between 2010 and 2020 [4]. Scientists analyze job ad data to better understand a variety of labour market issues, including how and when companies react to technological change, and hiring discrimination issues [2].

While some studies have sampled job ads across the entire labor market (e.g., [2, 8]), others have focused on jobs in the software engineering and information technology fields (e.g., [1, 3]). Daneva et al. [1] looked at the data from the three most popular Dutch IT job portals over the course of ten months exploring landscape of the requirements engineer specialists. Authors also revealed the most desirable skills and competences for such specialists. Gardiner et al. [3] sampled 1,216 jobs ads which included “Big Data” in their title. The researchers employed computer-aided content analysis and the consensus pile-sort protocol to develop a conceptual model of practitioner knowledge, skills, and abilities expected of Big Data job candidates. The study revealed the prevalence of traditional development skills in such job ads, reflecting that the development of analytics systems is the primary task for many Big Data specialists. The limitations of the study included the single point in time for the data collection, as well as the data being collected from a single job portal skewed towards technical jobs [3].

There are many ways to structure and classify the data collected from job ads. In their working paper on skill requirements across firms and labor markets [2], Deming and Kahn grouped the listed job skills in 10 categories: cognitive, social, character, writing, customer service, project management, people management, financial, computer (general) and software (specific). By identifying the skills expected of Product Ops professionals by the industry, our paper aims to determine in similar way the profile of Product Ops professionals. The study also assesses how well the above-provided definition encompasses the discipline. To structure and classify the data collected from Product Ops job ads, the 10-category topology of job skills proposed by Deming and Kahn has been adopted [2].

Table 1. Data sources
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2 Methodology

The paper aims to answer the following research question: What constitutes the profile of Product Ops professionals according to industry expectations?

To answer this question, we sampled job ads from two job portals: Startup Jobs and Glassdoor. Both portals were searched for job ads containing the keyword “Product Ops” or “Product Operations” in the title. Job ads that included additional term(s) between “Product” and “Ops”/“Operations” were not included, because these titles seem to imply a different focus of the role that might skew the result of the study of “Product Ops” specifically. The study analysed job postings from companies of all sizes and did not consider the geographic location of the companies posting the job openings. The study included Product Ops positions of different levels of seniority. The job ads were selected according to the following inclusion criteria: firstly, the job ads must be written in English, secondly, the job ads must include “Product Ops” or “Product Operations” in the title, and lastly, the job ads must specify working on software-intensive products.

Table 1 describes the number of search results on each job portal, the number of job ads selected, and the number of job ads analyzed during the study. The final sample included 30 job ads. Four job ads initially selected from Startup Jobs were excluded from the analysis because the product described was not software-intensive.

Once collected, the content of the job ads was manually analysed using Nvivo software. Only the “skeleton” of each ad was analysed, including sections such as “About the role”, “What you will do”, “Responsibilities”, “Qualifications”, “The ideal candidate will have”, “What we want to see in you”, and “What your day may look like”. Information about the company such as its history and standing in the market, as well as the benefits it offers to employees, was not included in the analysis. All skills, characteristics, and responsibilities described in the job ad were assigned a code. A degree of subjectivity was exercised in assigning the codes. For example, the following statements were all grouped under a single “storytelling with data” code: “Experience leveraging qualitative feedback to create product recommendations”, “You will regularly report to the leadership team to review the status of key initiatives, data regarding customer feedback and adoption of products, as well as other key business metrics.”, “Demonstrated experience synthesizing data to craft the narrative”, and “Generating visualizations leveraging different technologies to be included in slide decks and dashboards”.

After the initial coding of the 30 job ads was completed, similar or related codes were grouped according to the 10 categories introduced by Deming and Kahn [2]: cognitive, social, character, writing, customer service, product management, people management, financial, computer (general) and software (specific). While the 10 categories are mutually exclusive, they are not exhaustive [2]. In this study, an additional 11th category “Product Management” was added to address skills and responsibilities that fit within the SPM purviewFootnote 1. For example, the code “storytelling with data” was grouped under the code “Cognitive”, alongside “problem solver”, “analytical skills”, “excellent judgement“, and others. This grouping resulted in a profile of a Product Ops professional from an industry perspective. The remaining codes were grouped along the four dimensions of the formal definition proposed in [6] and presented in the introduction of this paper. This allowed for an evaluation of the validity of the definition by checking whether there is sufficient evidence in the job ad data to support it. Lastly, the impacts of Product Ops mentioned in the ads were grouped.

3 Results

The 30 job ads reviewed were posted by 29 companies. The most common position in the sample is the “Product Operations Manager” (8 ads), followed by “Director of Product Operations” (4 ads) and “Product Operations Analyst” (3 ads). Two ads look for a “Product Operations Specialist”, and two ads refer to the position simply as “Product Operations”. The remaining job titles were each encountered once: “Tooling Program Manager, User & Product Operations”, “Staff Technical Program Manager – Product Operations”, “Senior Program Manager, Product Ops”, “Senior Data Scientist – Insights (Product Ops)”, “Product Operations Associate”, “Product operations and Applications Manager” (sic), “Product Operations Analyst (Manager)”, “Product Operations Administrator”, “Product Operations (Consultant)”, “Head of New Verticals Product Operations” (sic), and “Head of Product Operations & Delivery Excellence”. Most of the positions are permanent. Only two of the ads specify fixed-term employment.

Almost every ad (98.3%) either requires or prefers candidates with some level of prior experience. Specifically, 63.3% seek experience within the particular software domain the new hire will be involved in, such as fintech, crypto-blockchain, or geospatial products. 36.7% necessitate previous involvement in data-driven decision-making, while 26.7% require former Product Management or Product Ops experience. Preference is given to those with a data-analysis background in 30% of the advertisements. A BSc degree or higher is required by 40%, although some ads accept industry experience as a substitute.

3.1 Product Ops Professional Profile

The recurring codes from the job ad text were classified along the 10 categories by Deming and Kahn [2], plus the added category of “Product Management”. The result is a detailed profile of a Product Ops professional from an industry perspective.

In the “Cognitive” category, a Product Ops professional is first and foremost a problem solver (mentioned in 60.0% of the job ads). They possess strong analytical skills (40.0%), and are data-driven (33.3%). They are able to craft stories from data (36.7%), are capable of multitasking (16.7%) and thinking on the spot (16.7%). Product Ops practitioners are comfortable navigating ambiguity (13.3%), are creative (6.7%), demonstrate critical thinking (6.7%) and have excellent judgment (6.7%).

Socially, they are excellent communicators (86.7%) adept at public speaking (23.3%) and possessing interpersonal skills (16.7%). If problems arise, Product Ops professionals know who best to notify, and use appropriate language depending on who they are talking to, for example avoiding technical jargon when dealing with executives (13.3%).

In terms of their character, Product Ops practitioners are proactive (46.7%) and detail-oriented (40%). They have a strong ownership mentality of the processes and initiatives they work on (40%), and are curious (30%) and motivated (30%). Product Ops practitioners are able to work independently (26.7%), and are organized (26.7%). They are adaptable (20%) and remain calm under pressure (20%). Ideal candidates are decisive (16.7%) and capable of learning to improve themselves professionally (16.7%). They are also results-oriented (13.3%), accountable (6.7%), and flexible (6.7%). Other traits mentioned include competitiveness, positive attitude, reliability, pragmatism, being an “active listener”, and exuding an “executive presence”.

In the job ads analyzed, 40% explicitly necessitate candidates to possess exceptional writing skills, applicable to tasks such as documentation, product training resources, and promotional campaigns. Product Ops professionals are frequently anticipated to engage closely with users and customers. 36.7% of the job ads portrays the position as user-centric, while 30% reference working in the interest of the customer. Explicit mentions of direct customer communication are present in 20% of the advertisements, and 10% indicate that the newly hired individual will be accountable for executing a Voice of the Customer (VOC) program.

A significant portion of job ads (33.3%) necessitates that candidates possess project management experience, while 30% explicitly require Agile methodology familiarity. Organizational skills are essential for 20% of the roles, with resource management responsibilities appearing in 6.7% of the ads. Within the “People Management” category, a Product Ops expert typically demonstrates cross-functional influence (36.7%), leadership abilities (26.7%), mentoring skills (13.3%), conflict resolution or prevention (10%), and is responsible for staff onboarding (6.7%). Ads call for previous people management experience in 6.7% of cases, with one job ad specifically mentioning involvement in interviewing and hiring. In the “Product Management” area, Product Ops professionals engage in product planning (43.3%), which encompasses roadmap development (36.7%) and requirements engineering (10%). They also contribute to product development (20%) and continuous product improvement (26.7%). A smaller proportion of ads (6.7%) highlight the importance of Product Ops experts’ involvement in product strategy development, emphasizing the need for a profound understanding of the products they handle.

A few skills are occasionally mentioned in the “Financial” category, such as cost-benefit analysis (6.7%) and capitalization analysis. Some positions mention the candidate would be in charge of ensuring financial compliance (3.3%) and involved in investment planning (3.3%). Product Ops professional must possess a general technical aptitude (“software (general)” from [2]) (33.3%), and work regularly with slide decks (16.7%) and spreadsheets (13.3%). Additionally, 33.3% of the ads require the candidate to be familiar with a specific software stack, and 30% state a preference for a candidate with sufficient programming skills. In the specific programming languages mentioned, SQL is the most widespread, being mentioned in 30% of the ads. Other languages mentioned are Python, Java, and R. Other programming-adjacent skills listed include familiarity with version control systems, CI/CD pipelines, command line, and low-code tools. Knowledge of software architecture and development life cycles is also mentioned.

3.2 Evaluating the Formal Product Ops Definition

To assess how consistently the representation of the Product Ops role in job ads adheres to the formal definition outlined in [6], the remaining codes identified in the job ad text were grouped along the four dimensions of that definition. Additionally, the impacts of Product Ops were grouped into their own category. The results can be seen in Tables 2 and 3.

In the Data Management dimension, the responsibility of Product Ops experts to gain insights from data is mentioned in 53.3% of the job ads. The involvement of Product Ops professionals in prioritization is mentioned in 46.7% of the vacancies, and their role of decision support is 43.3%. 30% of the ads state that Product Ops professionals strive for simplification within the organization. They are responsible for collecting data (26.7%) and feedback (26.7%), and overall data management (26.7%). Product Ops practitioners are involved in user research (26.7%). They are also responsible for setting up information repositories where everyone in the organization can access the data and resources related to the product (16.7%). Product Ops experts analyze the collected data to improve each iteration of the product, facilitating iterative learning (13.3%).

Table 2. The four dimensions of Product Ops
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Table 3. Product Ops impact
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In the Tool and process management dimension, 73% of the job ads state that Product Ops are in charge of measuring company processes to identify opportunities for improvement. Various aspects that are measured include performance measurement (56.7%), OKR tracking (43.3%), roadmap execution tracking (23.3%), and product status tracking (13.3%). 60% of the ads mention process development and process improvement as the core responsibilities, and 33.3% mention that Product Ops drive process adherence. Other responsibilities fitting this dimension include problem identification (33.3%), company and team tech stack management (30%), and internal tool development and management (23%). Automation (16.7%), obstacle removal (16.7%), and best practice development (10%) are also mentioned.

In the Operational complement dimension, the role of Product Ops as assistants to product managers and other company functions is mentioned in 26.7% of the ads. Product Ops help provide product support (16.7%) and troubleshooting support (13.3%). The impact of letting others do meaningful work by reducing the administrative burden and possible obstacles is described in 10% of the ads.

Finally, in the Collaboration dimension, 86.7% of the ads describe the desired candidate as an excellent communicator. A total of 83.3% describe Product Ops experts as the facilitators of cross-functional collaboration. Verbal communication skills are mentioned in 43.3% of the ads. The descriptions of the ideal candidate also depict a Product Ops professional as a partnership builder (40%). They are in charge of product documentation (36.7%) and standardization (23.3%). They act as a coordinator between various company functions, partners, and customers (20%), creating cross-functional feedback loops (13.3%) and managing cross-functional dependencies (13.3%). Teamwork (16.7%) and work with partners (16.7%) are also mentioned.

In terms of their impact on the company, 63.3% of the job ads require the Product Ops professional to increase the efficiency of company operations. Many of the ads (56.7%) state the need for Product Ops to identify new opportunities for product and process improvement. Another commonly mentioned impact is to help companies scale and grow (53.3%). Product Ops professionals are supposed to drive excellence and raise the quality bar across the organization (50%), and ensure the cross-functional success of company initiatives (46.7%). They drive OKRs (40%) and increase clarity around all aspects related to the product (26.7%). The desired impact of Product Ops is to facilitate communication (23.3%) and establish a culture of quality and high performance (20%). Other impacts described include the acceleration of various feedback loops, the improvement of feature adoption, an increase of the impact and visibility of company initiatives, and increased revenue. Table 3 contains the full list.

The Product Ops role, as portrayed in job ads, closely conforms to the formal definition proposed in [6]. The statement that “Product Ops [...] makes product companies more efficient and allows them to scale without friction” is certainly reflected in job ads, where “increased efficiency” is mentioned in 63.3% of the postings, and the “help scaling” in 53.3%.

The description of the data management dimension is also supported (“decision support” is mentioned in 43.3% of the ads). However, the “data cleaning” responsibility was rarely mentioned in the job ads – only one ad mentioned “data validation”. It may be implied in the “insights from data” (53.3%), “analytical skills” (40%), and the preferred data-analysis background (30%). The phrase “regularly receives” implies establishing a cadence for communicating with stakeholders, which was alluded to in some of the job ad descriptions and may fall under the “process development” category (60%). The optimization and alignment impact of Product Ops are also largely supported by the quantitative job ad data. “Optimization of time to learn from and react to insights and negative feedback” is reflected in “user-centricity” (36.7%), “iterative learning” (13.3%), and “accelerated feedback loops” (16.7%). The optimization of R &D costs is also alluded to in “prioritization” (46.7%), “identify opportunities” (56.7%), and “maximize revenue” codes (16.7%). The definition of the tool and process management dimension is supported by the “tech stack management” (30%) and “internal tool development and management (23.3%)” codes. The role of Product Ops in process measurement (73%) and improvement (60%) can be further emphasized in the definition, as it is overwhelmingly present in the job ads. The operational complement dimension is present in job ad data (“assistant” – 26.7% and “let others do meaningful work” – 10%), but to a surprisingly small extent. The proactive nature of the job is mentioned in 46.7% of the sources, and the supporting role of Product Ops in relation to other company functions is often alluded to. Finally, the collaboration dimension is largely supported by the job ad data (“communicator” in 86.7%, “cross-functional collaboration” in 83.3%, and “coordinator” in 20%). Product status reporting (40%) and increasing visibility (16.7%) also support the definition.

One aspect that is not explicitly acknowledged in the definition in [6] is the role of Product Ops in ensuring launch readiness of products and features, and management of software releases (described in 30% of the ads). The role of Product Ops in risk analysis on new initiatives is alluded to in 13.3%.

4 Conclusion

In this study, a total of 30 job ads for Product Ops professionals were collected from two job portals. The manual analysis of the job descriptions revealed a professional profile of a Product Ops expert based on the industry expectations for the role. A Product Ops professional is an analytical problem solver who is proactive and user-centric. They excel at communication in all formats and at all levels and can leverage that to exercise a cross-functional influence and build long-lasting partnerships. They can quickly and thoroughly analyze product data and craft a narrative that influences company decisions and moves the needle toward higher efficiency, quality, and revenue. The study also found that the profile of a Product Ops professional that emerged from job ads fits well with the formal definition proposed in [6]. The study recommended expanding the definition with the acknowledgment of the role of Product Ops in process improvement, ensuring launch readiness, and conducting risk analysis on company initiatives.

The study is subject to limitations. The sample size of the study is small, the data was collected at a single point in time, and the study is only a first step in a more comprehensive analysis of broader swaths of the industry. The numbers included in this paper were provided to clearly describe to the reader the picture that we observed in the analyzed sample. While the exact numbers are likely to change when more job ads are included into the analysis, we expect the list of the skills, qualities, and impacts to remain consistent with the present results.

During the manual content analysis of this study, certain recurring themes were noted but left for further study. One example is the organizational structures of the companies that practice Product Ops. Many of the job titles mention what department the Product Ops hire would be working in, or to whom they would be reporting. There are many ways in which companies structure their Product Ops function [6], and further analysis of this information could illustrate the various company structures.