Editor | On 19, Jun 2018
In Case Study: B2B Intangibles, we introduced the idea that, when it comes to the intangible aspects of any innovation attempt, the main success criteria involved making our ABC-M (Autonomy-Belonging-Competence-Meaning) tetrad â€˜get better for each stakeholder at each moment of truthâ€™. Really simple to say, much more difficult to achieve in practice. On the other hand, â€˜being difficultâ€™ should never be a reason for allowing oneself to fail to try and achieve.
This short article concerns the next stage of evolution of the â€˜ABC-M gets betterâ€™ story: the ABC-M Landscape.
The basic idea is very simple: identify the (moment of truth) steps in a process or journey; calculate ABC-M for each stakeholder at each of those stages; plot on a graph. Hereâ€™s what the resulting landscape looks like for a case we did for a recent analysis of the growing world of restaurant food home-delivery services:
Figure 1: ABC-M Landscape For Restaurant Food Delivery App Service
The point of mapping and showing the landscape is to assist the designers of the service to make improvements to that service. Knowing that (for example) the payment system makes people feel incompetent â€“ as is indicated in Figure 1 â€“ should be a spur to work out why, and then re-design the system such that they no longer have that negative feeling.
So much for the theory. The practice requires one or two additional thoughts in order to get the most out of the landscaping concept. Here are a few of the things we already know are important to get right:
1)Â Â Â Absolute versus relative measurements. Measuring intangible factors like a personâ€™s perceived level of Autonomy is very difficult in absolute terms. Fortunately, it is not necessary to obtain an absolute measurement for a given situation. What is rather needed is an understanding of the relative shifts between the different moments included in the pathway. The manner in which weâ€™ve taken to construct the figures is to make a starting assumption that ABC and M are datumed at a point just before the start of the journey. Weâ€™ve taken to datuming A, B and C at the same â€˜mildly positiveâ€™ level, and Meaning â€“ because it sits on a higher emotional plane than the other three â€“ at a neutral level. Having datumed each element just before the start of the journey, the basic questions to be answered at each subsequent journey stage are a) has the element got better or worse than the previous stage? and, b) has the element passed below a zero-line such that the stakeholder now possesses a negative feeling about that element. This zero-line thus forces us to establish whether a stakeholder has switched from feeling positive about their (say) Autonomy (â€˜I feel in controlâ€™) to feeling negative (â€˜I do not feel in controlâ€™) about it.
2)Â Â Â Start-And-End Of The Journey â€“ in the same way that we plot the landscape at a point in time â€˜just beforeâ€™ a process journey begins, we believe it is a good idea to end it just after the journey ends. What we are in effect aiming to do when we plot these two â€˜neutralâ€™ start and end points is explore whether there might be any residual after-effects of the journey. In most cases â€“ especially when doing something as mundane as ordering a curry on an App â€“ the expectation would be that the end ABC-M values would be the same as the initial datum. Where we find that the end value is different to the initial, it is an indication of the overall effect of the journey. In the case of the Figure 1 food deliver App service, the fact that Meaning at the end of the journey is lower than that at the beginning is indicative that the journey has reduced Meaning for the customer. Whereas one might have expected the food ordering journey to be merely â€˜meaninglessâ€™, it has in affect made life a little less meaningful. (A separate analysis of customer frustrations seemed to confirm this in that there was a degree of post-takeaway guilt on the part of, particularly, parents.)
3)Â Â Â Â Meaning-less â€“ look at the world through a â€˜Meaningâ€™ lens and you quickly realise there is an awful lot of meaningless stuff out there. Sometimes so much so that it is better to leave the Meaning characteristic off the landscape plot altogether. This seems to be especially true â€“ sadly â€“ in many workplaces (see Darrellâ€™s â€˜ABC-M Tetrads At Workâ€™ blog article). Rather than thoroughly depress people, better to create some kind of sense of progress by focusing on the ABC.
4)Â Â Â It probably wonâ€™t surprise you to learn that there is a PanSensic ABC-M lens and that weâ€™re rapidly reaching a point where we can construct and create these ABC-M landscapes in an automated fashion. The main challenge involves creating a journey ontology and training the system to recognize narrative that applies or doesnâ€™t apply to each of the stages. In the healthcare sector, where there has already been much work done on defining â€˜patient pathwaysâ€™ the job of plotting ABC-M landscapes is already made relatively easy. With other clients, weâ€™re in the process of building specific journey ontologies. Right now weâ€™re at a point where we need as many case studies as possible. If you think you have your target audience journey stages mapped, and you have lots of barely-analysed narrative data laying around doing nothing, the PanSensic team will be more than happy to talk to you.