Navigating the challenges of soft skills needs analysis: A guide for L&D teams

Why

• Values, mission and culture shape how employees behave and interact.
• Soft skills that align with these contribute to the achievement of your organisation’s strategic objectives. When employees possess and demonstrate these skills, they are better equipped to work towards shared goals, enhance teamwork, and contribute positively to the organisation's overall success.
• Organisations that consistently demonstrate the soft skills aligned with their values, mission, and culture tend to have a positive brand reputation, being perceived as trustworthy, reliable, and socially responsible. 
• This can lead to increased customer loyalty, business opportunities, and a competitive edge in the market.

How

1. Review mission statement, values, objectives and relevant documentation

• Review annual reports, employee handbooks and policy documents.
• Look for key phrases and words that describe the organisation's mission and values and identify how these align with its culture and goals.
• Identify key words relating to soft skills.

2. Survey key stakeholders

• Gather information from senior leadership, business managers, and HR teams.
• Use data from employee and customer surveys.

3. Gather data from job descriptions, competency frameworks and performance management systems

• Look for soft skills mentioned as desired or required for various roles. 
• Identify recurring themes or patterns related to soft skills and assess how they reflect your organisation's values and desired behaviours.

Why

• The workplace landscape is constantly evolving and skills needed will radically change. 
• Soft skills are increasingly important to success, enabling organisations to adapt and thrive in a dynamic and uncertain environment, preparing their employees to navigate future challenges and drive sustained growth.
• By anticipating future skill requirements, organisations can proactively prepare their workforce for upcoming challenges and opportunities by bridging skills gaps. 

How

1. Plan 3-5 years ahead

• Stay up to date with Future of Work trends. 
• What are the most popular skills on the rise in your industry?
• How mobile and transferable are key skillsets? Can they easily shift to different departments or geographic locations?
• Which jobs in your organisation will most likely become automated in the future?
• What kind of roles (that do not exist today) will be most urgently needed?
• How prepared are you for unexpected turnover of valuable skillsets (e.g., digital skills)?

2. Create future skills frameworks

• Prioritise the skills that will have the most impact on your 3–5-year plan and link to your mission, values and business objectives.
• Consider how you can leverage technology to help you create both future skills inventories and a training needs analysis.

3. Integrate future frameworks into current skills map

• Update your skills maps with these high-priority future areas. 
• Consider using talent management systems to audit future as well as present skills needed against the current capabilities of your different teams.

Why

• Psychological safety provides an environment where employees feel comfortable expressing their thoughts, opinions, and needs without fear of negative consequences. Employees can openly share sensitive topics and reveal skills gaps, for comprehensive, accurate and valuable information.
• It also fosters trust between employees and the L&D team, increasing engagement in the needs analysis process and subsequent soft skills training. 
• Open and honest sharing encourages a culture of continuous improvement and learning that supports ongoing soft skills development.

How

1. Reiterate the purpose of soft skills analysis

• Highlight that the aim of the needs analysis is to support employee development and meet their training needs. 
• Explain how the gathered information will be used to develop targeted training.
• Emphasise that it is not part of performance management.

2. Reassure employees that open, honest input is valued

• Let employees know that there are no consequences of sharing
• Demonstrate that you take their input seriously by using non-judgmental active listening and empathy in focus groups and interviews and recognising their contributions to surveys

3. Provide clear communication and expectations

• Be transparent about the process, timeline, and any potential follow-up actions. This helps employees understand the value of their participation and builds trust in the process.
• Assure employees that their responses and feedback will be kept confidential where possible.
• Offer the option for anonymity, particularly in surveys or assessments, to further promote a sense of safety and encourage honest and open responses. Let employees know if you will share data on their specific soft skills gaps

Why

• It’s important to ensure the reliability and validity of information so that actions can be focused and effective. This can be challenging when gathering data from large numbers of dispersed employees. 
• Striving for unbiased data collection, promotes fairness, equality, and inclusivity in the research and decision-making processes.  
• By avoiding bias, L&D teams can enhance trust, foster confidence in the data, and maintain their reputation as reliable sources of information. 
• Personal beliefs and biases of assessors, impartial tests and assessments, and user bias can all influence data quality and integrity. 

How

1. Avoid social desirability bias

Employees may give responses they think will make them look good (socially desirable) instead of their honest answers. They may overestimate their soft skills, leading to inaccurate results which undermine the needs analysis effectiveness.

• Emphasise the importance of honest and accurate responses by assuring them that responses are confidential.
• Use a variety of data collection methods including interview and behavioural assessments to provide a more comprehensive view of soft skills ability. 

2. Avoid groupthink bias

Employees from certain teams or groups may conform to the opinions of the group instead of expressing own opinions. This can happen in focus groups or team meetings.

• Invite a facilitator to guide the discussion and ensure all voices are heard.
• Ensure group needs analysis is complemented by individual, anonymised analysis

3. Avoid cultural bias

Needs analysis tools and techniques can be biased towards certain cultural norms or assumptions. E.g. Perceptions of effective communication differs between cultural contexts.

• Ensure needs analysis tools and techniques are culturally sensitive and appropriate for all employees.
• Translate assessments and surveys.

4. Avoid confirmation bias

Surveys, interviews, or assessments could be unintentionally structured in a way that elicits responses that confirm their beliefs, inadvertently leading to biased results. 

• Check for neutral and balanced language when designing or procuring surveys, interviews, or assessments. 
• Conduct pilot testing to identify and address potential biases. Use feedback obtained to refine and improve the data collection methods.
• Collaborate and seek others’ input to minimise biases stemming from personal perspectives. 

Why

• Balanced data analysis ensures that decisions and conclusions are based on a comprehensive, objective and unbiased understanding, providing accurate, reliable insights, leading to informed decision-making.
• By striving for assumption-free analysis, L&D teams can minimise the risk of misinterpreting or misrepresenting the data.
• Transparency about methods, procedures and decisions allows others to assess the validity and reliability of your analysis and helps foster trust in your analysis and decision-making. 
• This enhances the credibility of and confidence in the insights and recommendations presented.  

How

1. Approach the data with an open mind

• Maintain an open and unbiased mindset and be willing to challenge assumptions and preconceived notions. 
• Avoid making premature conclusions or forcing the data to fit a specific narrative. Instead, let the data speak for itself and guide your analysis.

2. Validate and cross-reference conclusions

• Validate your findings through multiple means. Use a range of techniques, cross-reference data, seek input from colleagues and use industry benchmarks 
• By cross-referencing the data and seeking diverse perspectives, you can reduce the risk of biased interpretations and assumptions.

3. Look beyond the surface-level data

• Identify patterns and themes in the data that may indicate deeper issues or trends

4. Practice transparent reporting and documentation

• Clearly document the steps taken, assumptions made, and any limitations or uncertainties encountered.