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Design Thinking for Business Innovation  Juber Millet

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I lead an initiative in my organization to automate the various tasks spread across phases in the  software development life cycle. Each phase of the life cycle has many a task and automating these  tasks need to be measured for the effectiveness of the automation tool and technique. While the  most obvious measure is reduced turnaround time and cost savings, it always does not mean that the  automation is effective. From an organization perspective while the cost is an immediate gain, the  customer experience plays an important role in defining the strategy. Any organization initiative has  to meet both tactical and strategic expectations and my endeavor was no different. While the  programs are concerned about the immediate gains within their tenure, the organization’s view is  long term, way beyond the lifetime of the product that it provides its customers as the feedback has  a bearing on its brand image. Hence, what is used as a metric should address needs at varying level  and across a long time frame. The chosen metric should articulate the effectiveness of automation to  be accepted across a range of stakeholders.    Selection Selection Selection Selection     From a wide variety of metrics recommended by industry experts, I had a problem of plenty – to  choose the most relevant and most effective metrics. While each metric had its own merit, the means  of recording and ease of reporting given the different systems of record used across the organization  and customers differed hugely. To address this challenge, I sought inputs from the major programs  across the organization, thus ensuring the adequacy of data quantity. Seeking the reports in their  current form helped me to allay the doubts on their quality, as these reports have been accepted by  both our organization and our customers. With the data in hand, I had all the inputs to identify a set  of effective and acceptable metrics. To ensure that I was not affected by confirmation bias, I  presented my proposal – the what ifs? – to the experts who have experience in working both with  the programs and the executives in the organization. This exercise helped me to distill my findings  and present a refined and succinct list – which has wowed the stakeholders.      Experi Experi Experi Experience and outcome ence and outcome ence and outcome ence and outcome

Using mind mapping as a technique proved to be an effective tool to pouring out my thoughts and  findings into one huge set of possibilities and the associated pros and cons. It helped me draw  comparison of all the metrics, providing me a view of patterns across the way they are measured,  recorded and reported. This technique provided me insights into the differences and commonalities  across different programs and also provided me with an overview of the challenges and opportunities  all in single view. Even as I was aware of mind mapping, this experience opened up a new horizon of  its applicability. Learning how to effectively launch a pilot helped me to finalize the most effective  metrics by engaging groupthink and avoid confirmation bias. I am now confident that my proposal  will serve the need of programs and of the organization alike. The ease of measurement and reporting  for the programs and for the organization, to showcase the success of its automation strategy will  assure the customer’s delight and look forward for more business. The course helped me look into  applying design thinking in a way I couldn’t imagine.

