LEARNING LAUNCH Of PROPOSED SERVICE OFFERING BLUEPRINT

CHALLENGE

I recently took over a role to incubate new service offerings in my organization. We, as an  organization currently do not have any similar offering that can be used as a foundation to evolve or  create what we want. Being a globally recognized thought leader in this technical domain (service  management), I have been entrusted with the responsibility to come up with the new service line  that is apt for the Next Generation of business services. I had already ideating and creating the  service blueprint before taking the Design Thinking sessions. So, the key challenges that I wanted to  address was:

•  What we conceptualized, would it really sell with our existing or potential customers (will  they really appreciate what we are bringing forth for them)?

•  If they do, would our execution blueprint really work?

SELECTION

I wanted to:

•  Test our idea, our blueprint

•  Identify what works and what does not

•  If fail, fail fast → Learn →Refine → Mature → Scale

Thus, I was determined to conduct a series of small experiments with our selected customers, with  each experiment meant to validate a hypothesis based on one of the core components of our new  service offering. Hence, I needed to test the key assumptions that went into the creation of the  blueprint, and thus the service offering blueprint itself. Inspired by the video on IBM Story, I decided  to use ‘Learning Launch’ as the tool to conduct the experiments and eventually refine our blueprint.

APPLICATION

Our proposed service offering constituted of a number of elements, each of which were required to  be tested & validated independently as well as the way they perform in an integrated fashion. So, I  created hypothesis that we needed to validate for each of them. I worked with my delivery  organization to identify the customers (10 customers were identified based on their interest and  agreement from varied industry domains) to whom we can take our service offering blueprint and  collaboratively refine the same. Since, I wanted to experiment and see what works for us and what  does not in minimal time, I grouped the offering elements and related hypothesis. We assigned a  priority (based on criticality and urgency for readiness of the element for launch) to each service  element that steered the way we grouped them. We experimented this set with one customer and  another with the another one. The purpose was to:

•  Maximise the elements that are being experimented in parallel

•  Learn and refine what does not work before experimenting with the next customer  (initiating the next stage of Learning Launch)

•  Minimize financial exposure and risk

Below figure depicts the approach we took to run our hypothesis testing in parallel.

The way we applied the Learning Launch tool is diagrammatically depicted below

As represented above, I created a hypothesis for each service element which drove the set of  assumptions that I wanted to validate. We tagged each offering elements and thus the hypothesis to  be tested to a customer and the sequence in which the other customers would be approached for  experimenting the hypothesis. Our goal was to experiment each service element with at least 5  customers and then decide if there was a need to take the experimentation to other customers. This  fundamentally formed the next stage of our Learning Launch. We designed the way in which the  experiment would be performed. E.g. for a service element, we did the following 5 key activities  collaboratively with our customer SMEs and resources:

•  Refined the customer’s policy & process in a joint workshop

•  Mapping the value chain for that element/hypothesis being tested

•  Identified when, where and how the value was created (if not then why → fed into  refinement of our proposition); Also steered the way we represented and called out the  value, benefits and outcomes

•  Identified the challenges that affected the execution and the way we managed them → fed  into refinement of our execution strategy

•  Identified the dependencies (in some cases, we realized this as part of challenges) → fed  into refinement of our execution strategy with better articulated dependencies

To execute the experiments, we grouped our SMEs based on their experience and expertise. I  ensured that our goal is clearly understood by our team so that we all worked towards our common  goal.

Data from the experiment was used to refine our overall proposition – commitment towards value  creation/benefits, execution strategy and the dependencies on as well as expectations from various  stakeholders. This also attributed to refinement of our go to market strategy that was meant to scale  our service offering.

INSIGHT

As described in the previous section the insights gained from the experiments has helped us to  refine our overall service proposition. But in addition to those it changed the way we were  approaching our customers with our service offerings. 3 key ways our overall proposition changed  were:

•  We realized that our Service offering can be industry domain contextualised easily; some  elements were domain contextualized during the experimentation phase

•  We recognized that a number of smaller or sub-service offerings can be created providing a  quick win as well as a significant potential financial return for our organization; This even led  to creation of a number of service packages

•  We identified new ways in which the value was being created and more importantly the way  our customers appreciated the value.

APPROACH

I would prefer to continue with my approach as ‘Learning Launch’ gave us compelling benefits for  the service elements that we have tested. So far, we have been able to experiment 12 core  components of our Service Offering blueprint based on the priority that we had assigned to them. We  are continuing with the experimentation of other elements and intent to complete that by end of this  quarter. Results from the previous Learning Launch initiatives has convinced us that this is the best  approach for completing the testing of our complete offering. Additionally, it has triggered an  interest in the organization for testing the current relevance and feasibility of some of our other  ideas too. One thing that I would preferably want to change for experimenting the remaining service  offering blueprint would be to have more customers from each industry domain as it would help me  in having a greater confidence on my domain contextualized offerings.

