In a previous post I covered the “hard” ROI on BI initiatives. I discussed aspects that you can measure to determine the value that these initiatives directly contribute to the “bottom line” of the business. In this post I investigate the “softer” intangible contributions that BI can make, but these aspects are also much harder to quantify and gauge, never mind assign a monetary value to.
Under the soft ROI of BI we generally consider aspects that improve the experience of customers, staff or stakeholders. Unlike process efficiencies, which can typically be measured, the customer, staff or stakeholder experience is hard to measure and gauge correctly. What constitutes a positive customer experience, may not hold much water on the staff satisfaction scale. Customers may want ease of use, comfortable and quick navigation – on any device, while staff, on the other hand, may require a breadth of service, depth of information – i.e. level of detail, data accuracy and prompt information delivery.
And then, we have to factor in peoples’ moods. We can surface the best information at the right time in the right business process, but if someone is experiencing a bad day, it is hard for better formatted or more timely information to really improve their mood and hence the experience directly. But of course, not having the correct information in the right format at the right time can similarly cause them to have an even worse experience. Keep in mind that it takes many positive experiences to offset one such negative perception or even worse for a real setback.
Another of the soft ROIs of BI is improved inter-functional collaboration, based on inter-departmental information being more accessible to role players across the business’ functional boundaries. So yes, we can measure the amount of information shared, but that is not the real soft ROI. We may sense that there is improved collaboration between business functions, but how can we possibly measure it?
Some aspects of soft ROI can be gauged – note I didn’t use the word “measure” though. Aspects such as customer satisfaction, the “wholeness” of the customer experience, employee and staff satisfaction, and cultural fit can be gauged through surveys; and the results of the surveys can even be tracked over time to determine whether the experience has improved or deteriorated. Of course, most surveys are also subjective, and as with the example above, the mood on the day (or the time of the day) can also affect the survey responses. Sometimes, even a badly formulated survey itself can affect the ratings given. For example, in the current age of instant gratification, who has the patience to fill in a 40-question survey?
I have often spoken of applying BI to BI data, but likewise, we can employ social media technologies and sentiment analysis to implement a much simpler and today-relevant style of survey. If you can connect with your customers or staff on social media, you can post one single question like “Are you satisfied with our service?”, or “How can we improve our service?” In the current age where people love to give their opinion, you’ll be surprised how much insight you can get from the set of responses to such a simple prompt. In a case study we recently did for a client, we could identify requirements for new features, opportunities for cross-selling, and of course, how their customers felt about the service they were getting – which in turn, pointed out where the client should improve. By applying text analytics to the responses, we could extract what features they are interested in, by applying sentiment analysis we could determine how they experienced the service, and by applying BI overall to the data gathered from the responses, we could significantly increase the usefulness of the survey, all from a single not too intrusive prompt.
In the end, that is a very useful way to gauge the soft ROI on BI as well.
