The first thing that the group should do is to agree the organization’s and individual departments’ objectives and requirements, and these should be expressed in business or operational terms. For instance, in the case of one of our clients, a large broadband cable operator, the Field Operations Department claimed that a GIS solution would reduce the number of site visits required during the sales process because of access to integrated and better documentation. Plus where a site visit was still required, the time required per visit would also reduce. These operational benefits can be linked to financial benefits and we will see how in the following sections. At the same time, the Sales organization claimed that by better targeting of prospects close to or on the existing network, their sales force would be able to sell more effectively. The Engineering Department said that the consequence of targeting prospects close to or on the network would reduce the average capital expenditure required to build out to the new customers. These GIS benefits would not only trigger cost savings but could also be directly linked to sales and market share growth through sales conversion. The team now has two sets of data: one set of goals and objectives and one set of potential benefits. For this particular client we identified over 25 potential benefit areas, covering operational costs savings, revenue growth and capital expense reduction. This set of goals and benefits provides the organization and the GIS implementation team with:
After building consensus on the benefits and objectives with the multi-disciplinary team, the challenge is then to quantify identified GIS benefits from a financial perspective. The potential GIS benefits are far-reaching and are generally more visible for those closer to the technology than to others. To counter this, the team must identify the key operational performance metrics related to the benefits identified in the initial step -in essence this is converting the business stated benefit to financial measurement language. For instance, using our broadband cable operator client example, when the Sales organization says that GIS will increase sales effectiveness, they should attempt to quantify how the sales conversion rate will be affected, i.e. how many additional prospects will each Sales Rep convert each month? Likewise for the Engineering Department, they should try to estimate by how much the number of site visits would be reduced, and the average duration of the site visits. All these estimates provided by operational, marketing, and financial staff forms the base for the ROI Model to be built. The benefits of this bottom-up approach is the fact that key business and function experts get involved in the ROI assessment process earlier on and therefore own the assumptions within the financial model. Given the large number of assumptions, it is essential to link each assumption to a key owner or stakeholder. This allows the GIS team to create robust foundations for the business case. After having documented all key assumptions, the challenge is for the team to link these to financial performance indicators, such as revenue, cost, and capital expenditure. The idea is to be able to draw a link from an operational performance indicator to the ROI generated by GIS, as demonstrated in Figure 1. For instance, going back to the sales conversion rate benefit, by linking the increase in the conversion rate to the number of potential customers and average sales per sales rep, the financial manager can estimate the increase in revenue (and impact on ROI) generated by the implementation of GIS. Likewise, using the engineers’ reduction in site visits and site visit duration, the financial manager can link these to the hourly cost of each site visit and estimate the potential cost savings for that specific operational benefit. Again, that cost saving impacts the ROI directly.  Figure 1 - Links between operational and financial benefits and ROI |