“Information” in a broad sense is structured, processed and organised information. It gives context to already existing data and helps individual decision making about future course of action. For instance, a particular customer’s sale in a restaurant is data especially if the company is able to segment the customers into groups according to factors such as: average spending, special requests or number of visits. Data can also help people in decision making as it shows trends over a certain period of time and how sales are going.
A well presented data series can highlight differences between predicted values and actual values for a variable. This could be used to analyse the effect of a change in one factor on job gains or total compensation. This example could also be used to explain the difference between predicted versus actual wages.
An example to explain the above example would be using forecasted job gains to forecast the growth in total compensation in line with increases in union membership. Using forecasted values, the HR team can analyse their organisation and see what would happen in the future if they continued to follow a traditional Recruitment and Employee Development (R&D) strategy with a high level of employee turnover. Using forecasted values, they can adjust the investment in training, improving the quality of candidates hired and take other steps that will bring down the cost of recruitment without impacting the quality of recruits.
To interpret this example using the data series back data examples above, assume that the forecast is made for a medium term investment strategy with investment in new processes and staff over three years, totalling a minimum of twelve staff. The assumptions can be varied as per the needs of the organisation and the current trends in the economy. Assumes can also be made about the future level of union membership and corresponding impact on the attractiveness of recruits for the prospective employer. Where there is significant variation across the assumptions used in the forecasting exercise, caution should be exercised due to the potential outcome bias that could occur as a result of the model assumptions being different from the true economic factors.
One of the first steps taken by any HRM organisation in setting the investment strategy is recruiting the right people for the right jobs. This requires access to a wide variety of data sources on the skills and attributes of the candidates, their organisation, and their personal characteristics and preferences. Data on skills and preferences are sourced from interviewers, existing data on job gains and the number of people with those skills and preferences available in the market, data on the current job market and the quality and quantity of jobs available in the market, the current economic and social environment in the target area and the competing jobs in that area, and a variety of other sources. The analysis and evaluation of the data back to determine which areas require additional investments focus and effort can take a great deal of time. It is for this reason that organisations must have a method for gathering, aggregating, and analyzing data in a way that maximises return on investment and minimises the likelihood of future administration and management problems related to investment strategy decisions.
If future investment decisions depend on the value of the assets, the total compensation packages that are proposed for the candidates in the recruitment process can impact the attractiveness of those candidates to potential recruiters based on their total compensation package. Assuming total compensation packages of say one million pounds, it is easy to see that the attractiveness of a candidate increases or decreases by approximately ten percentage points for each additional thousand pounds paid. Therefore, the methods that an HRM organisation uses to analyse the data back to determine how the assets, including the total compensation package, will influence the ability to attract and retain the best talent can become important to the success of an investment strategy. All this analysis and evaluation of data needs to be carefully monitored and researched to determine the HRM organisation’s strategy’s ROI.