Organisations are constantly seeking to improve their return on investment in people and increase their profitability. Les Pickett shares some practical guidelines to help HR professionals prepare a business case for human capital investments
Step 1: Be clear on the business need. Identify the business outcome(s) that you are seeking to improve or target. These could either be financial outcomes (such as sales, revenue, or costs) or non-financial outcomes (such as safety, customer satisfaction, or employee retention).
Step 2: Think through the methodology. The business outcome(s) that you are seeking to improve will determine the methodological approach you should take. It is important to ensure that the level of “business outcome” data corresponds to the business need you are targeting. For example, if you are seeking to improve sales, your methodology should be designed to analyse the “human drivers” of variations in sales effectiveness across sales offices within your organisation. In other words, because your analysis will focus on sales offices, your data collection (see step 3) should be designed with that in mind.
If, alternatively, you are seeking to reduce employee turnover, your methodology would be designed to analyse the human drivers of variations in turnover across managers within your organisation. In this case, your analysis will be focusing on managers, and your data collection needs to be designed accordingly. As a general rule of thumb, the more granular the business outcome data that you use, the more precise and compelling will be your business case. For instance, your analysis will be much stronger if you focus on variations in employee turnover rates associated with individual managers, rather than turnover rates across larger departments or functional units.
Step 3: Get the data you need. Obtain data on the business outcome(s) you have selected at the appropriate organisational level (as discussed in step 2 above). You should get the most recent data available, while ensuring that it incorporates a sufficiently long time period (typically, at least a full year) in order to remove the effects of random “noise” in the data. At the same time, gather (existing or newly acquired) employee survey data (which should include multiple items that are possible “human drivers”) and calculate each item at the same organisational level selected for the business outcomes data (eg, by sales office, by manager, etc as discussed in 2).
Step 4: Think about the data analytics. Next, you must select the method that you will use to statistically link the business outcome(s) with underlying human drivers. The specific statistical methods that are available for you to choose from will depend on the nature of the data available to you (eg, amount and quality). They range from the simple (eg, comparing the difference in average values of the human drivers between high- and low-performing units) to the complex (multivariate, time-series analysis).
Step 5: Analyse the data to identify relationships between drivers and outcomes. For each business outcome of interest, use the technique(s) selected in step 4 to analyse the magnitude and the significance of the relationship between each employee survey item and the business outcome(s). Rank these items (human drivers) in descending order of their importance (magnitude/significance) in shaping each business outcome.
Step 6: Identify organisational strengths and weaknesses. Using the same data from your employee survey, rank in ascending order your organisation’s strengths and weaknesses on each survey item.
Step 7: Simultaneously consider key drivers and organisational weaknesses. Examine the rankings developed in steps 5 and 6 to identify those human drivers that are simultaneously among the: (a) most important in determining your organisation’s business outcome(s), and (b) areas of greatest weakness in your organisation. (It’s going to be difficult to get a whole lot better in areas that are already among your greatest strengths, so it makes sense to target the most important areas of weakness).
Step 8: Identify your priorities. Based on the joint ranking that emerges from step 7, choose a shortlist of items that meet both criteria and are thus among the most important for you to spend time and resources on improving.
Step 9: Create a shortlist of solutions. Identify the specific interventions (eg, training, coaching, process improvement, modifying your performance review system, executive development) that hold the greatest promise for improving those key drivers of business outcomes where your organisation currently has relatively low capability.
Step 10: Develop estimates of cost and benefits. Identify a range of both the likely costs of the proposed intervention(s) along with the likely business benefit. Calculate the “worst case” outcome by dividing the lowest likely benefit by the highest likely cost, and the “best case” outcome by dividing the highest likely benefit by the lowest likely cost. This will generate an analytically responsible range of low-end and high-end estimates.
Les Pickett is partner, Australasia and South East Asia, McBassi & Company. Email: email@example.com