How do you ensure the reliability and validity of your market pricing data?

Key factors to consider include: Methodology: Choose surveys with a transparent, sound methodology to ensure data reliability. Participants: Opt for surveys featuring companies you compete with for talent, ensuring a relevant data set. Job Inclusion: Ensure the survey covers roles pertinent to your organization's current and future needs. Job Leveling: Alignment with other surveys you use is crucial for creating market composites. Industry Data: Balance industry-specific surveys with general ones for a well-rounded view. Data Source: Favor employer-reported data over less reliable crowd-sourced information. Legal Compliance: Ensure the survey adheres to Safe Harbor and antitrust guidelines.

Job matching is a valuable tool for ensuring effective market pricing in compensation strategies. By using it effectively, organizations can attract and retain talent, build fair and competitive pay structures, and make informed decisions about compensation.

La fiabilité de la donnée est clé. Pour ma part, je m'appuie sur un outil payant agrégeant un grand nombre de données en temps réel, sur l'ensemble du marché européen. La déclinaison de ces données, poste par poste, avec un détail en fonction du niveau de séniorité, de la taille et du secteur de l'entreprise est essentielle pour disposer d'éléments de comparaison pertinents. Point de vigilance : le benchmark n'intègre pas toujours l'ensemble des éléments de rémunération d'un package. Il faut donc bien savoir quelles sont les éléments intégrés ou non dans les chiffres du benchmark pour prendre du recul sur l'analyse par rapport à la pratique interne.

While looking into sources for your market data I try to keep in mind these key points: 1/ How your Org is matched and weigh jobs. All jobs in surveys are same (even if the title is similar) nor do they have the same level mapped 2/ What method do you take into consideration when matching, do you take incumbents or organizations, do you apply premiums to one survey and discounts to others, ect. 3/What time do you need the data by. When picking surveys be aware of the return date. If you are picked surveys that don't return results back in time, then that's not a good match over all for the Org. (depending on the desired out come of the data)

Companies should start by evaluating their entire job architecture as a foundational step in aligning to market. Unless jobs are correctly leveled and categorized by family, matching to external data will be inconsistent at best. Think of the challenge of matching unstructured data to structured data - you have to add structure to your unstructured data as a first step. Market pricing is no different.

It might be tempting to take a shortcut and match by job title only. Don't make this mistake. Matching by job title alone leads to apples-to-oranges comparisons, providing little value to your benchmarking outcomes. There's a real ROI on the time spent to properly match based on job content.

Carefully match your job roles to the survey roles based on job content, responsibilities, educations, years of experience, and requirements rather than the jobs title. Accurate job matching is crucial for obtaining valid market data that truly reflects the roles within your organization.

When matching jobs to survey jobs, having a firm grasp of Job Duties is a must. Partner with your business units, your Talent Acquisition teams and the HRBP/Generalist to make sure your matching correctly. You could be over paying or under paying depending on that outcome.

Pay decisions should be informed and not dictated by market data. In my experience, companies without a clear talent strategy and comp philosophy tend to over-index on market data by asking "what are other companies doing?" without having a point-of-view on what actions might be most appropriate for their particular organization. Organizations that just try to imitate competitors miss out on a unique opportunity to design compensation programs that differentiate themselves from the competition.

Be sure your methodology is defendable and repeatable. When your analyzing data, it shouldn't be a feeling or a guess. The ROI and Time associate with this portion is mission critical in my opinion. Look at the market data, age it appropriately, apply any band premium or discounts and look at the big picture. Depending on the Org goals, you should meet with your Leadership team to review a few scenarios based on impact on market shift and company outliers effected.

Conventional wisdom has been to review your data once (or maybe twice) per year. This is largely driven by the time intensive nature of each review process. Given the influx of new market pricing tools being built by various vendors (which is great!), I can envision a not-too-distant future where market pricing happens at a more frequent cadence...or perhaps even an "always on" eventual setup. Of course, the downstream implication of "always on" market pricing is how frequently to run a merit cycle ("always on" merit cycles are probably bad for numerous financial and cultural reasons). But the more on top of market trends that heads of total rewards can be, the more effective they will be at their jobs.

When evaluating external data sources for compensation, I focus on credibility and relevance. First, I check the source's reputation. Established salary survey companies with proven methodologies earn more trust. Second, data relevance is crucial. For example, focusing on surveys targeting my specific industry (e.g., tech) and geographic location (e.g., San Francisco Bay Area) ensures the data reflects the competitive landscape I need to understand. Finally, I consider the survey's sample size. Larger samples with diverse participants provide more reliable compensation benchmarks. By examining these factors, I confidently leverage external data to create competitive compensation strategies.

To ensure the reliability and validity of your market pricing data, source information from reputable, up-to-date salary surveys and market studies. Cross-verify data from multiple sources to identify consistent trends and outliers. Regularly update your datasets to reflect current market conditions. Employ statistical methods to analyze data accuracy and consistency. Additionally, consult industry experts and use benchmarking techniques to validate your findings, ensuring they are aligned with industry standards and organizational needs.

Regularly reviewing and updating market pricing data is essential for maintaining its accuracy and relevance. Market conditions, economic factors, and industry trends can change rapidly, impacting the competitiveness of your compensation structures. It's crucial to establish a routine schedule for data review, whether annually, every 18-24 months, or on an as-needed basis. During these reviews, reassess your job matches to ensure they still align with market equivalents. Pay attention to changes in job responsibilities, required skills, or industry standards that might affect job comparability. Also, consider any internal organizational changes, such as restructuring or new roles, that could impact compensation benchmarks.