Following Trends!
As a PM starting out afresh you’ve been asked to go on an implementation spree over leveraging latest trends in technology & finding ways to fit it in. What would you do?
Disruption - A Market Trend!
Considering what’s happening w.r.t disruption in the technology space with most organizations in the world keeping a close tab on and moving towards what is trending and also adopting to them seamlessly into their workflow, there is a whole necessity for product teams to either innovate themselves or hop onto innovative platforms over what’s touted as the next big thing. Virtualization is where it all started from when the Cloud based Tech has disrupted the space completely turning it on its head and SaaS has acted as a precursor and a backbone around which it all functions be it any kind of a SaaS / PaaS / iPaaS application to all the LowCode, NoCode tools.
Here are some of the advantages of switching over to Cloud-based technologies:
And here is a graphical representation of the adoption patterns of the market and where we stand today and how the future projections look like in this space.
A TAM of 10 trillion over a super bullish scenario in the years to come looks a reality given the disruption rampant in this space as of today.
But, all of this has to start from somewhere and have some roots of semblance, some facts and learnings to hinge upon and translating them to workable action plans, isn’t it?
Let’s double down straight into that over the next section.
PM work tends to Rationality
Talking of a start-up organization that’s predominantly into building apps and platforms using the latest of technology, they would want to explore “any” route that’d take them towards their goals of successfully getting a whole lot of the market to adapt and jump over to the platform monetizing it suitably. When its only but natural for leadership & management to think like that, the whole onus is on the PM team to get it right wrt all of these factors:
1. Goals
2. Technology
3. Markets
4. Fitment
5. Alignment
1. Goals
Starting off with trying to get a deep understanding the goals of the organization is a complete task in itself and it requires some skills and experience to decipher and break down information from those ambitions / goals to courses of action / plans and strategy.
When the management / leadership at the top may be used to and predominantly talk in terms of figures, businesses & outcomes it becomes important to understand whether they have an area of focus particularly. And, if they do, it is about exploring, researching, interviewing, fact finding to get to a level of understanding of where you stand wrt your product currently.
So, before you get to understand goals you may first be required to gather tons of information branching out and covering all of these parameters in detail. And one word for all of this is RESEARCH.
Research could be of 2 types:
Primary Research – where you personally goto the market and conduct research by observing, talking to, interviewing users / user groups of your addressable target market
Secondary Research – where you resort to information searching over the multiple channels like the internet / any other print medium to find facts supporting the hypothesis / theories you have about your market
2. Technology
When things like AI / ML, Bigdata started out some years back almost everyone in the market wanted to implement it some way or the other jamming it into their workflow.
Guess what!
Users don’t really fall for things like that, and just supposing they did initially they’d eventually churn if any such new tech isn’t adding any chief value to them over what they thought it would be / what they were promised earlier.
To combat that, you’d have to first start by understanding the technology in some depth and its capability (pros and cons).
You may not need to get into the nitty gritty of coding, architecture but you could scope the possible ways and means in which a certain new trending technology could be employed and also the limitations over the problems it’d be able to solve. That done, you’d just have to align them over the needs of your organization and the pain points your market has at that particular moment vide exploring it over desirability, feasibility, viability.
Supposing your product is using IoT employing sensor-based technology and receives a lot of continuous data streamed in from those devices on the field. And if you now want to implement ML to build predictive analytics using regression I’d totally understand the alignment as it is an extension, a natural course.
But, let’s say you are a furniture shop selling D2C through a storefront / online web shop and you want to use ML to bring up / feature the most popular product choice across your entire customer base, I don’t see the necessity there. A simple select query with some basic selection criteria would work very well in this case.
Complication was, is & should never be needed in any business.
3. Markets
This could indeed be the trickiest part of the entire lot because this is where you subject your thinking to the test over taking it stepwise and analyze how the world reacts to it, whether it is received well or not.
And, the reason I say that it is tricky is it is very easy for someone to assume / even have proven supporting data and facts that XYZ technology could solve the problem in a certain manner for a certain segment of the market containing a certain sample space of users.
But, that assumption has to be floated around the market in an aim to understand what your current user base thinks of it whilst also exploring the feasibility of having such tech built at your end in terms of a budget and pricing strategy because great tech products could come down and hit the ground crashing if the markets feel that it is too expensive or there is something cheaper available that they could employ to solve their problems.
Factor the market’s voice trying to cover all parameters that could perhaps influence a user’s / buyer’s decision even before you start thinking of building a team required for developing that next great tech product because if the price isn’t feasible even the greatest technology could remain great on paper and would be good for featuring just over every other magazine cover without any sales.
4. Fitment
Yes, it is important that your product fits in with the market and the ecosystem of products already being used.
Market fitment or product market fit is actually beyond that as there are many cases and examples where some products have successfully disrupted the market in the way they were going about their workflow till that point and got hooked on to a completely new product post it’s release. That’s because of the innovation it brought about in the way those perceived benefits and perceived value addition was rendered. Also, the new product had switching costs baked into their strategy that was successful in tying down the users for a longer period of time.
So, fitment should not be a onetime thing but a long term strategy in helping the organization attain a level of sustainable growth making it easier to build and launch products and features for a longer period of time to target customer loyalty and this whole activity underpins how crucial research is in gaining this understanding and also how teams need to be on their toes wrt baking the right amount of innovation into those features time and time again whilst having a robust backlog to keep the market captivated over a long period of time.
5. Alignment
Am sure most of you love burgers.
Ask yourself how you’d feel if your favorite burger joint started another product across the counter (over a kiosk) that allowed you to take an appointment with a doctor.
Firstly, the idea itself doesn’t go well with a food joint that’s selling food across the counter to say:
“Hey! Welcome to our food joint. Yes, we have a lot of food options available for you to come over and enjoy”.
But guess what!
“In case anything goes wrong with your health we have a doctor handy as well right here”.
As opposed to say the same food counter that gets into a partnership with a shopping complex and books a spot there, reopens the same counter because their analysis showed that they didn’t have an impressive footfall or they had just a shady percentage of the footfall a neighboring building / mall gets.
Alignment doesn’t mean doing things exactly according to what management / leadership has in mind. It ought to involve reshuffling of the what, how & where of your product offering so that it helps move the needle over the required metrics.
In gunning for a level of rationality and clarity over things to do as a part of drafting a plan for all the other teams to align and follow, a framework like a Business Case Canvas could be apt and a nice place to start.
Case Study – Twitter
Here we’ll explore the business model of a very common social networking product that is Twitter and also understand all the parameters that make sense to think about in the pre-build (ideation & planning) stage.
A business case canvas captures information by tying all of the 5 points discussed above alongside other important factors predominantly over a these 3 main points:
Market & the user’s underserved needs
Product & the related factors
Value proposition(s) that grossly tie the above two
Conclusion
Whatever the circumstances, stick to your ground and gun for more clarity on all of the 5 parameters mentioned above before moving in towards any kind of solutioning / product build activity.
And never swallow verbatim of anyone either internal / external stakeholders / members of teams concerned. If anything, use the verbatim as a premise in probing and understanding more about the emotions and motivations.
Link to the original tweet: Twitter status - Guru Prasad