Reflection - Mind Map

Challenge  I work in Software Sales as a Presales. Sometimes the people that test and want to buy our  software are in more technical roles. They see a high value in using the software, but to be able  to buy it they need to convince a decision maker to give them a budget. For this, they have to  pinpoint the business value that using this new software would generate - time saved, money  saved, new revenue generated etc. . They also have to evaluate the software in order to show  that the value is really there and not only theoretical. Our team helps them to define the success  criteria for such an evaluation (among other things).  When talking to the data science team of company X, they already approached their  procurement department, because they wanted to buy our software. The procurement  department told them to formally evaluate the software, and to involve the proper budget holders,  in this case the chief of marketing and the chief operating officer. So, our goal was to plan an  evaluation of our software, including a list of success criteria, together with the data science  team.  We would then present it to the budget holders before kicking off the evaluation. We had  to keep in mind that everything would be done remotely due to the pandemic.    Selection​:   A visual approach like a Mind Map facilitates collaboration while working remotely. We would be  able to start with a blank slate, without influencing the data science team with our assumptions.  Nevertheless, we could make suggestions during the process. As a result, we would get an  organized hierarchical structure from which we could pull the success criteria for the evaluation.    Application   We planned a 90min online workshop to define the success criteria for the evaluation. For  preparation, we asked the data science team to write down 3-5 points each that they think would  be benefits and risks of using our software - what would they be able to do, that they can’t do  now, and what would have to change? To kick off the workshop, we wrote all these points down  on a blank page and then helped them to organize these into topics, e.g. faster processes,  impact on productivity or integration with other tools. During the emerging discussions, new  points and topics came up. Additionally, we suggested further points and topics that they didn’t  think about first, like collaboration with other teams, bringing projects into production or  compliance with regulations when accessing data. The result was a hierarchical picture of the  relevant points that would have to be evaluated in order to make a rational decision. We wrote  these down as a list of success criteria.     Insight​ & ​Approach  The end result was a list of success criteria specific for this evaluation and this customer. But the  workshop took longer than the planned 90min. Luckily, we could just go on and extend to  130min. Even with the ‘homework’ before the workshop, it took more time than planned to list all  the relevant points. We thought that the customer would know their business better than we did,  and that we should only chime in with additional topics after the data science team didn’t come  up with any more topics. This led to a slow start of the process, resulting in a longer workshop.   For the next customer, we provided the customer with a list of topics (that in our experience are  always important or have to be thought of at least) before the workshop. We asked them to write  one or two points down for every topic, and to also think about other topics that might be relevant  for them. This helped a lot in making the workshop itself more efficient, and also provided more  material for interesting discussions and new ideas during the workshop.

