Example Reflection –Learning Launch

Challenge

This reflection is based on a case from my experience with a service organization. The company  offers maintenance and repair services of industrial equipment. When service engineers are on site  they often find equipment potentially mature for replacement (end of operational life).

With the project my team and I wanted to set up a lead generation process - implemented in  company's CRM - to target modernization opportunities for the above category of assets

Leads would come in from service engineers via a mobile app. One important requirement was to  design a process with little overhead for service engineers and technical sales who would engage the  end-customer. However the registered information had to be relevant to enable a meaningful  engagement. Services and sales organizations were involved in the project and they were my internal  customer.

Selection

We could not kick off a full project involving a large number of resources without having the process  right, and a demonstrated upside.

The team, me included, did not have much experience with Design Thinking, however we worked  agile and we planned for several refinements. We had few interviews with our customer - a relatively  small subset of the service engineers and tech sales - to define the process, understand the  workflow, the required data set, what we needed to report and measure, lead times, and hit/win  rates, etc. Our hypothesis was that a proactive and facts based engagement with the end customer  would lead to higher hit/win rate, above historical average.

We then wanted to focus on learning and measuring these rates through a live process, therefore we  run a learning launch.

Application

After the process was defined, we briefed and planned the learning launch with the selected  engineers and sales reps.

We used a progressive approach. We first simulated the data pushed by service engineers into the  CRM, we created mockup leads and forwarded them to the sales reps to receive feedback on data  quality. Thereafter we verified that service engineers could indeed and with low overhead (5-10 min)  provide such data. There were two important outcomes from this step:

  Taking pictures of the equipment was agreed to be a quick way to provide much of the required  information (rating labels, serial number, visual inspection, type of environment, etc).

  Often a challenge for a service engineer was to figure out end-customer relevant contact  information, such as service manager, operation manager, facility manager, etc. so that tech  sales could engage with the right person at the end-customer. This could be solved by enhancing  the information in the "back office"

We then set on the learning launch as such, which was planned to last two months. The chosen  service engineers were enabled to push data of candidate assets by using the mobile app. The lead  was received in the CRM as an email (at this stage of learning launch). It was then examined and  enhanced in the back office by my team by looking up databases of known assets and customers. If  the lead was qualified, it was then forward in the CRM to a sales rep who tried to engage with the  end-customer.

Insights and approach

By the end of the learning launch we got more than 200 leads from candidate assets. We learnt the  percentage of qualified leads and of those representing actual business opportunities with their  value. We gather additional requirements for the improvements of the front-end app and the  automation achievable in the CRM platform to enhance and qualify leads, thus reducing transaction  cost.

We also discovered hidden expectations f.e. the need for a fair incentive scheme for service  engineers (sales reps have naturally one) who were creating incremental value for the company. We  had a stronger case, as we proved the hypothesis; we better understood the implications and the  cost for implementing the process in production, as well as the incremental value for the company.  As I write the lead generation process has been running for a couple of years with significant business  upside.

In conclusion, this Design Thinking course made me aware of the importance of the "learning  launch”, as a powerful tool for minimizing risk of “failing late and expensive”.  The scope of a learning  launch can be adapted, by selecting internal customers - in an early phase to learn quickly and cheap  – vs. external end-customers to learn from real life feedback. I would say that learning launch is a  robust end-to-end testing approach, which ought to be used in any new product or service  introductions.


Example Reflection – Learning Launch Challenge This reflection is based on a case from my experience with a service organization . The company offers maintenance and repair services of industrial equipment . When service engineers are on site they often find equipment potentially mature for replacement ( end of operational life ) . With the project my team and I wanted to set up a lead generation process - implemented in company 's CRM - to target modernization opportunities for the above category of assets Leads would come in from service engineers via a mobile app . One important requirement was to design a process with little overhead for service engineers and technical sales who would engage the end - customer . However the registered information had to be relevant to enable a meaningful engagement . Services and sales organizations were involved in the project and they were my internal customer . Selection We could not kick off a full project involving a large number of resources without having the process right , and a demonstrated upside . The team , me included , did not have much experience with Design Thinking , however we worked agile and we planned for several refinements . We had few interviews with our customer - a relatively small subset of the service engineers and tech sales - to define the process , understand the workflow , the required data set , what we needed to report and measure , lead times , and hit / win rates , etc . Our hypothesis was that a proactive and facts based engagement with the end customer would lead to higher hit / win rate , above historical average . We then wanted to focus on learning and measuring these rates through a live process , therefore we run a learning launch . Application After the process was defined , we briefed and planned the learning launch with the selected engineers and sales reps . We used a progressive approach . We first simulated the data pushed by service engineers into the CRM , we created mockup leads and forwarded them to the sales reps to receive feedback on data quality . Thereafter we verified that service engineers could indeed and with low overhead ( 5 - 10 min ) provide such data . There were two important outcomes from this step :  Taking pictures of the equipment was agreed to be a quick way to provide much of the required information ( rating labels , serial number , visual inspection , type of environment , etc ) .  Often a challenge for a service engineer was to figure out end - customer relevant contact information , such as service manager , operation manager , facility manager , etc . so that tech sales could engage with the right person at the end - customer . This could be solved by enhancing the information in the " back office " We then set on the learning launch as such , which was planned to last two months . The chosen service engineers were enabled to push data of candidate assets by using the mobile app . The lead was received in the CRM as an email ( at this stage of learning launch ) . It was then examined and enhanced in the back office by my team by looking up databases of known assets and customers . If the lead was qualified , it was then forward in the CRM to a sales rep who tried to engage with the end - customer . Insights and approach By the end of the learning launch we got more than 200 leads from candidate assets . We learnt the percentage of qualified leads and of those representing actual business opportunities with their value . We gather additional requirements for the improvements of the front - end app and the automation achievable in the CRM platform to enhance and qualify leads , thus reducing transaction cost . We also discovered hidden expectations f.e . the need for a fair incentive scheme for service engineers ( sales reps have naturally one ) who were creating incremental value for the company . We had a stronger case , as we proved the hypothesis ; we better understood the implications and the cost for implementing the process in production , as well as the incremental value for the company . As I write the lead generation process has been running for a couple of years with significant business upside . In conclusion , this Design Thinking course made me aware of the importance of the " learning launch ” , as a powerful tool for minimizing risk of “ failing late and expensive ” . The scope of a learning launch can be adapted , by selecting internal customers - in an early phase to learn quickly and cheap – vs. external end - customers to learn from real life feedback . I would say that learning launch is a robust end - to - end testing approach , which ought to be used in any new product or service introductions .