Today one can hardly argue that IT investment is a significant aspect of a company’s strategic planning. Recent technological outbreaks have enabled managers to collect and handle any amounts of data records. The question, thence, arises, whether the informational interpretation might present any significant value for a firm’s performance. Thus, the necessity of developing efficient measuring tools such as the Return on Information metrics is explicable.
Applying technologies for data analysis can either increase or decrease the information value depending on the efficiency of the selected approach. Thus, current research shows that the usage of the most modern and advanced machinery devices does not essentially guarantee the data cost advance.
Nor does the type of data collected determine its utility for the improvement of a firm’s performance. Analysts tend to consider management functioning to be the key factor that preconditions the success of the ROI policy. Thus, managers of huge corporations claim that the vast digital data volumes are highly problematic to be turned into valuable insights that can be further used as the basis for budget scheduling.
According to the results gathered from several case studies, effective ROI is only possible on condition that one deals with “the right information, from the right sources” (Mattocks 2013, par.5). Nevertheless, while modern technical equipment is not a pledge of successful information managing, poor IT policy is apt to decrease the value of data available. Return on Information analysis is to be preceded by profound targeting that will help to turn the relevant metrics into significant marketing indicators.
As far as the success of Return on Information metrics application is determined by the objective setting; it is logical to suppose that ROI is to be managed by the strategy marketing department likely to handle the issue most efficiently. It is crucial that the company invests enough money in the employment of high-qualified analysts able of performing a precise evaluation of the data operating.
Even though modern technologies are capable of processing any amounts of digital data, human factor still plays the key role, as it is a person responsible for the critical analysis of the received results.
Whereas, the machinery sorts out the necessary statistics, a good specialist turns it into the materials valuable for the company’s performance. Thus, ROI performance requires organized cooperation between the head management that is supposed to define the objective and the professional analysts that can provide the demanded results (Pavlou et al. 2005).
Basing on the experience, one can point out several challenges that appear when measuring the ROI. First of all, companies are likely to face unforeseen expenses due to the hidden costs that the selected approach implies. Secondly, the abundance of sources available makes it a hard task to identify the most reliable one. Moreover, the choice of the search platform is frequently neglected as the non-important fact.
This disregard can seriously complicate the process of data handling. Finally, ROI calculating is often performed within the wrong factor framework, whereas the only relevant criterion for ROI estimating is the value of the information. The data validity assessment is not always properly performed. There are numerous cases when the analysts fail to evaluate the information’s cost in the relation to the set objective.
The so-called “Informational Age” requires the development of new approaches to the information operating. ROI assessment is to imply a complex of measures aimed at receiving a full database concerning the informational value, the justification of the IT investment, the congruity of the current management strategy. The ROI analysis is to be performed with consideration of the firm’s policy and budget peculiarities.
Mattocks, R 2013, Marketing ROI Starts with a Return on Information, <https://www.lyntonweb.com/blog/bid/87909/Marketing-ROI-Starts-with-a-Return-on-Information>.
Pavlou, PA, Housel, TJ, Rodgers, W & Jansen, E 2005, ‘Measuring the Return on Information Technology: A Knowledge-Based Approach for Revenue Allocation at the Process and Firm Level’, Journal of the Association for Information Systems, vol. 6, no. 7, pp. 199-226.