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Step 6: Seeking Value

· 12 Steps

In our last Step (Step 5), we looked at work breakdown as a social art. In Step 6 we want to continue in that vein by asking how do we seek value as a continuous activity without a spreadsheet or a conventional ROI? We can make value-seeking part of our everyday activities and a key behaviour

The fundamental question - how do we seek value - is routinely overlooked when teams set up projects. Even when executives give a green light to a new line of work there is little thought given to how the project will unfold in a value-driven way. Rather it is assumed that the project as a totality has value and therefore the main task is to complete it.

But what if the project soon looks like a dud? Or what if many of the components of a project block value rather than add to it?

We talk about value seeking as an everyday behaviour in order to counter these problems. We don’t want to do work that has no value or chase a project to an unsatisfactory end.
 

We’ll use a couple of examples from the book here in Step 6 to see how we go about doing that. In the process we are seeking 80% of the value from 20% of the resources while discarding unvaluable work. Those are our overall objectives along with what economist call Pareto Optimisation.

So here, we are going to look at seeking and creating customer value. The information applies equally to internal project or infrastructure.

When we talk about customers we generally mean anybody who is a potential beneficiary of value creation. But the key is that value is seen through the customers’ eyes.

Some value stories

In the 1970s and 1980s the United States’ television receiver industry came under sustained attack from Japanese manufacturers. Just to be clear the “receiver” is the TV set.

 

American companies like RCA had built substantial integrated businesses on the back of black and white TV set production and program production but had really pioneered the mass production of colour TVs. They all went bust! By the 1990s those companies had lost out to Sony and co, before the Japanese began to cede ground to South Korean manufacturers.

 

What was the secret of Japanese success?

 

First, in this period, US companies introduced a lot of semiconductor technology to the TV set and the Japanese happened to be better at learning how to optimise semiconductor manufacture. They did continuous learning much better.

 

But second there was a different kind of optimisation. US companies drove towards excellence, producing TV sets with the highest possible image quality. The Japanese optimised rather than maximised. US-made TV sets had a high rate of valve burnout caused by the demands of that superior image. That meant customers had to call out the repair-engineer regularly. The Japanese had optimised to ensure less valve burnouts and less repairs.

 

The streaming distribution network Netflix has optimised the design of the servers that it supplies to cable companies and telecoms companies for storage of popular films and series. The servers are especially rugged and expensive and that gives them both a long lifespan and less need of repair. In fact Netflix does not repair them and does not manage a field engineering workforce, saving a fortune in overhead.

 

These are examples of looking for value across a matrix of activity rather than driving for efficiency in any single, or discrete, area.

 

They are also beautifully simple ideas that have helped create world class companies.

 

In FLOW we similarly look for how a mosaic or matrix of activity is best optimised.

 

Flow Optimisation Analysis

In the world of manufacturing engineers talk about value-stream analysis. This is a highly detailed review of all processes where engineers will seek ways of taking out waste.

Despite its name it is rare to use such an analysis to ask: Are we actually creating value here? Or, are we optimising the way we create value?

In FLOW we have begun to talk about Flow Optimisation Analysis where we ask precisely those questions. A Flow Optimisation Analysis is a periodic sanity check on the work we are doing. It has that Value Stream element - can we get rid of waste. But it has a big difference too.

In Flow Optimisation we are asking people to keep an open and curious mind in order to address the bigger question: Does what we are doing make good sense, in that it creates value and it does so in a good and balanced way?

The optimisation review is periodic and assesses the value-logic of features and functions that have been in place for a while. But first we need to learn how to create optimised value. That’s what we’ll concentrate on now.

Value propositions and value seeking

Very often in business the idea of value is framed as a value proposition.

Value propositions are another example of business literature being dominated by the needs of startups or new products. Bear in mind we are seeking something different: How to maintain a continuous flow of innovations that we can test with customers.

The usual way to define a value proposition reflects the fact that startups don’t have customers. Here is a couple to chew on, one from Forbes:

In its simplest terms, a value proposition is a positioning statement that explains what benefit you provide for who and how you do it uniquely well. It describes your target buyer, the problem you solve, and why you’re distinctly better than the alternatives.​

And one from the dictionary:

an innovation, service, or feature intended to make a company or product attractive to customers​

We think of a value proposition as something much more complex and encompassing. You can see from the examples we gave of Japanese TV manufacture and Netflix servers that the value proposition is also the search for value in the optimisation of resources.

The idea of a value proposition being a singular statement of value and uniqueness is quite different from the position many, if not most, large companies find themselves in.

In established enterprises the search for value arises in two main ways.

  1. How can I be sure that my work-in-progress and projected investments are adding value to customers in a balanced or optimised way? That can also be framed as: How can I be sure my activity and investments are helping my customers to succeed with their lives and that this is sustainable (economically, for us, environmentally, for the world, and morally, for society)?

  2. What initiatives can we develop to expand our markets as new technologies arise and new needs become evident?

We’ll leave position 2 alone for now and focus on position 1.

The key question is:

I have a substantial amount of work-in-progress, and more in the backlog, more still in the Portfolio plan, so how do I assure myself that each work unit we embark on is helping customers to get what they want or need, especially as I transition to new ways of work (the Flow Optimisation Analysis would ask that retrospectively)?

Seeking value without writing value propositions

The normal way that companies go about creating value is project-based. We’ve already argued against this.

The reason is simply that projects have a beginning, middle and end with a number of reporting obligations imposed on them. They are so formalised and over-burdened by management tools and reporting that they have become the wrong units of work for the modern enterprise.

Projects typically fail or disappoint because they are an inappropriate management framework for innovation, certainly in today’s climate.

We advocate, instead, a continuous flow of activity in units of work that are overseen or managed because they are visible and they are open to the scrutiny of peers, their social interaction and their collective intelligence.

Remember also that we advocate breaking work down into units over a period of time, also in a very public way on Business Walls. But we don’t think of this as a hierarchy. We think of it as a series of conversations about value.

Figure 1. A schematic of work breakdown for value

We avoid the idea that any of the units of work that follow from this are projects that have a separate life from the search for value.

So the question we asked in the book was how do you take business objectives and work them into value?

Like work breakdown, it is partly an art. But the idea of value brings discipline to what you are doing. Here are two examples.

Changing the system cycle in insurance

Because large firms have multiple systems in place, there is often a system-cycle that goes with innovation.

Again the literature eides this point. We talk instead about technical debt - ie keeping up, or not with the innovations of our corporate peers.

The real problem though is that certain types of innovations have a system-wide impact. Imagine electric vehicles and the impact they are having on the system of distributing gasoline and electricity. Imagine the hydrogen car and what that will do to the system.

Systems protect incumbents but there are times when the roots of innovation are so obvious and the need so great that the system becomes surprisingly malleable. That’s what’s happening with drones in insurance.

In FLOW we touched on the likely future use of drones to help collect information about traffic accidents and in the process to add value by being an independent observer of events following an accident.

However, drones have become quickly adapted by insurance companies in part because of the increase in bad weather events. Insurers have always been well set to deal with a periodic catastrophe but such events are increasing in frequency, placing claims and settlement systems under unbearable strain. Drones can help resolve that crisis.

They are now playing a role in providing data for better underwriting of risk; assessing claims after an event; speeding up the payment of claims; and speeding up the process of compiling claims for the ultimate underwriter, the Lloyd’s Syndicate.

The development of drones in this application area has been rapid, beginning in 2014.

It is difficult to portray this development as a minimum viable product that built iteratively towards a new product that a company put on sale.

Reaping the benefits of drones is iterative in the sense that improvements in drone software continue to hone the performance for this application, improvements in data integration and software will continue to improve claims processing for years to come; and adverse events will benefit from faster adjuster cycle-time.

There’s not much doubt about this. The issue is how to get to highest value in the fastest way. And that seems to be progressing in the way we suggest many value-creating processes do. The question of value is being broken up into many parts and it is being tested all the way.

Insurers are working with small expert firms in the field of drone applications to iterate and build the experience of dealing with quicker and better data, how that can be integrated into insurer processes (or how those processes need to change), figuring out how to develop and manage a drone fleet, what compliance issues arise, where and when to deploy, and how to adopt machine learning to help deal with the scale of data that drones will create.

Each of these would become a matrix of mini-two-day units of work in Flow.

In short, this is not a product development cycle, it is a system-cycle that has multiple strands and layers of innovation that need to take place simultaneously and where the constant question will be to discover where the best value lies.

Creating value in transport

Here’s a second example:

In the car industry much of the R&D, marketing and advertising goes into selling cars, usually through distributors. However, much of the profit comes from selling parts.

We pointed out in Step 1 of this 12 part series that the car industry is tolerably good at customer segmentation for sales. Curiously it is the luxury car makers (most obviously BMW and Mercedes) that are particularly good at segmentation. However, few car makers are good at segmenting their after-sales customers.

An additional problem arises when distributors upsell too aggressively. A car maker’s credit portfolio can be badly strained by that temptation, in effect blighting the brand when the letters start arriving reminding a car owner to pay the monthly credit bill.

To summarise:

  • Many enterprises do not have problems that can be solved with a startup approach such as MVP.

  • They struggle to balance complex psychological and financial pressures.

  • After-sales is where the profit lies.

  • Car makers have little idea how this market segments other than data on the types of cars that get serviced most.

  • Car makers think they can solve this problem with a big data solution, or “markets of one.”

In Step 1 we pointed out that there are plenty of opportunities to address the key problem differently.

The business goal is to bring customers back to service garages well beyond the point where their warranty expires.

This clearly conflicts with the success factors that shape customer behaviour.

Distributor servicing is often more expensive than the neighbourhood garage; the experience is rushed and sometimes aggressive, it is often on the edge of town and customers struggle to organise transport into work or back to pick the car up.

On the other hand the neighbourhood garage offers very few guarantees.

The idea of the big data project is to find out what motivates people who keep returning and to see if those success factors can be spread around to other customers.

This is a very technology first way of looking at business. If we settle back and start to articulate the business objectives they should be something like:

  • To find ways to enhance customer success in different segments

  • To bring happy customers back to the distributor service centres

  • To provide an enhanced experience.

Looking back at those five steps to work breakdown, we would use the Wall to articulate these goals and the ways they might be reached.

Phase 1. The Statement of Proposed Value

We articulate a set of general statements about the market segments, the problems, the technology, the options, success factors and so on.

By looking at the segmentation we can see new opportunities. Let’s just focus on one.

As we pointed out in Step 1, females disproportionately follow after-sales on social media. There is something in here that smacks of opportunity for more customer success.

Very often in business people are thinking of “kind-of” and “somehow”. Of course, it would be perfect if the value and how it might be acquired were both absolutely clear. But generally they are not. You have to play out a hunch.

Is there an opportunity to enhance the some segment of the female experience of after-sales support, attract word-of-mouth marketing for our services, increase the retention through and after the warranty period, overall raise parts and service revenues and through this positive experience create more excitement around the brand?

As well as these valuable sentiments, we need a $ value for this opportunity. And it could be our goal is to increase female retention rates by 10% overall and understand female success factors across each segment of the market so that we can understand how to improve success across the market.

We could also set other objectives. As the car industry grows more towards a platform business we could argue that we need experience of developing new partnerships and ecosystems. Who else could provide solutions for us in this area?

Phase 2. Articulating the goals

Outside the world of formal project management, no goal is ever static. We know what we want but we’re prepared to see the objective change as we understand more. And bear in mind this opportunity sits along many others we’re working on.

In this case we want to find ways to encourage women to experience distributor servicing in the most positive way possible.

We might bring in sociologists and/or psychologists to help us understand what success factors look like for different segments of the female after-sales market.

The questions we begin to ask concern the culture of distributor garages, as well as transport to and from distributorships, bearing in mind the proposition that more women favour after-sales than favour buying. All these go up on the Wall.

It’s clear that several units of work can be built out of observing behaviour at garages. We can use closed circuit TV or paid observers to do that. But we want to articulate the work so that we are getting results after two days and not two months.

Our research experts pitch up at the wall to exchange ideas on how best to glean insights without a huge amount of wait time.

  1. One goal is surely to understand more. We want some kind of travel diary for people attending garages - how far do they come, what means of transport, at what cost?

  2. Part of that is to dive into market segmentation. We want to segrate this into male/female and into work types (manual, office, executive or some other segmentation).

  3. Another goal is to get a handle on the customer experience. We want to observe interaction at a cross section of garages.

  4. We want to do some exit polling, i.e. asking customers what could have been better as they pick their cars up.

  5. Another goal is to look to the future. We want to throw a curveball in there - what do younger people think of this environment, the next car buyers?

  6. We want to understand what different solutions might come out of this, and we can do a lot of anticipating before we get the results. We need to project different solutions, for example, do we need to provide better online information about the car’s life cycle and value cycle or maybe personal safety? Would a mobility website help and if so how?

  7. A key business goal is to get users to become advocates. We need to answer the question: How would success play out on social media?

  8. Another goal is to increase our capacity to develop partnerships. There may be new product opportunities or partnerships with apps like MyTaxi (offering discounts from the garage?) or at least looking at the coverage of car ride apps around distributorships.

  9. We want to integrate with existing data sources. We need to tie the research into the insights we have from our onboard apps in order to scale any benefits quickly.

  10. We really want distributor staff to be more alert to different customer success factors. There could be additional online training modules needed for distributor staff.

  11. We want to drive our go-to-market model right to the heart of the project. That means designing each component as an opportunity for customers to advocate and share good experiences, which in turn has to feed into every aspect of the experience we want to design.

  12. We start to speculate about some form of gamification where customers earn points or some other reward based on their interaction with us. Maybe this is the answer to the survey problem. A suggestion goes up on the Wall to have a Twitter campaign offering $25 off a service in return for completing a survey within the next 48 hours. Currently we see them once every six months but a more continuous relationship will allow us into a relationship where they earn better pricing and now we have a reason to get out there on social media to connect with them as co-designers of a new level of service.

  13. We need a way to monitor the value creation both from a customer’s perspective and our own - are we headed to our 10% improvement target and how can we be sure?

  14. We want to be a little bit left field. Assume cost is a big issue for female customers, are there new forms of payment that the garages should experiment with? Can we learn from Amazon Prime?

  15. We want everything to scale. What opportunities exist for collecting new data to help scale solutions up?

  16. And we need to understand impacts. There will be implications for software architecture.

All of this is taking place on a public Wall and so far we haven’t spent more than a couple of hours.

Phase 3. Capturing User Success Factors

In Agile this would be called writing the user stories and some of what we have gone through above might fit into an Epic, though Agile does not really have the same relentless fix on value as Flow does. However, in Step 3 we are closer than in the other steps.

We have to ask how can we understand the overall work activity from different perspectives? But we have to go further than that and ask what are their success factors?

The Angle: Where does value lie and for whom? The customer is one user but the system includes distributors, garage managers, mechanics, payment systems, taxis. Though we can’t spell all this out right now we do have an opportunity to ask which of these activities gives us the shortest route to value (for customers)?

What would tangibly add value to the outcomes they want to achieve: From a car driver perspective: Is it savings on a service, improving residual values, just getting to the garage more easily or cheaply, is it flexibility in scheduling, being less confronted by gender insensitivity, or what other success factors do they have?

From a distributors service manager’s perspective: Is it to be sure of maximising service throughput each day; is each day already maximised, is there an optimal alternative to maximisation (for example is the imperative to maximise throughout each day at the cost of upsetting customers who then don’t return), is there anything on the cost of customer acquisition that we can learn about that would help persuade distributorships to optimise rather than maximise?

From our own perspective: is it to minimise architectural impacts while meeting those business goals?

In normal project planning we would already have progressed to the schedule of activities according to our sense of a production sequence drawn from the world of manufacturing - what has to be done first and what follows on in sequence from that (that’s how we go to PERT and GANNT charts).

Iterating the business goals. As you can see in Flow we are still asking questions and allowing ourselves the time to be curious about options. We want to focus on where we can clearly gain value.

As the tasks and questions come see more light the process creates a mini-inflection point for the business goals. We run into the inevitable questions about how sound those business objectives are. And where are the clear priorities, based on our desire for maximising value early?

If a business goal looks like it is going to take a long time to achieve, we need to get a sense of its value and whether it is worth the wait. We need to consider adapting it, if value is too far down the track.

For example, looking too far to the future might cause delays in creating apps that users willingly share. In any case we can probably get some very valuable insights into customer needs, as well as stimulate business, if we act quickly on the research and say, do a two day Twitter research project that gamifies a survey, offering extra coupons for filling in more questions. Maybe we can combine this with the idea of the travel diary?

Designing that survey, setting up the automated analysis, and then figuring out the meaning could all fit nicely into two days work a piece as well as give us a clearer idea of customer success factors. But isn’t it better to get the team to go out and exit poll people at garages?

Meantime we can begin looking at what it might take to integrate some form of customer interaction with taxi apps.

Any customer interaction we design at this stage should also take into account the wider system of transport. We are looking at capturing user success factors rather than applying our success criteria.

What would a car maker’s mobility website look like? Could be very interesting to scale up engagement around car care, mobility options, optimising travel arrangements, and residual car values.

The conversation goes on around the Wall as IT engages Marketing and Strategy in these conversations.

And each of these raises questions about units of work.

The Go-To-Market Model. In most traditional IT there is inadequate attention paid to how a development (unit of work or minimum sustainable delivery matrix) will get to market. Not all work is aimed at markets either because it will be infrastructure based or be aimed at migrating technologies.

All that to one side there is a good deal of work that directly relates to end customers who pay for our services.

When people design intangibles they tend to stick to their silos. Business hands over a set of requirements and IT goes build. But now we have feedback loops from the call centres and social media and we could have better segmentation. We have the capacity to create units of work to help us seek out value but what guides all this?

We already said the idea of value itself is a good guide but you could add in a go-to-market model (GTM).

Large enterprises with tangibles will think of that as marketing, sales and advertising, the distribution network, the retail outlet or a B2B channel and so on. And the GTM will be a calculation of how much it will cost, through which channels and to which segments, to get enough units sold in what space of time to earn a return.

In Flow we think instead of how to market efficiently. Design should be guided by a customer’s willingness to share information about a service, to recommend it.

In the book Flow we set out 12 points of a GTM but suggested that you might have your own. A central part of this is building in Long Tail tools such as:

REVIEWS

RECOMMENDATION ENGINES

SURFACING LONG TAIL CONTENT

PERSONALISATION

SHARING

DYNAMIC PRICING

GAMIFICATION TO IMPROVE EXPERIENCE

There is more to a GTM than that - like how will customers discover your product and how can you design in discoverability? What is the start and end of the customer journey? But that’s in the book. Just be aware that those ideas can help guide value-based design.

Phase 4. Creating Units of Work

In Step 4 we are looking at creating units of work that can be handed over for research, marketing and production.

The truth is, many organisations lack the degree of integration between these teams that would give you a rich work breakdown where marketing, business delivery and IT tasks appear on the same Walls.

In an IT environment the objective is to get your work breakdown to the point of simple statements of a user’s needs.

In a broader and more multidisciplinary project we have more scope to seek out value. Intuitively we might believe it lies in how servicing is paid for or how people arrange transport to and from the garage.

We can start breaking those down into units of work.

This will be a series of cards we short statements on. In an IT environment these tend to be very short agile-like user stories such as:

As a customer I want to be able to log-on.

That then becomes a coding task. Or

As a customer I want to be able to watch a video on the page.

In the broader environment we need to articulate a wider variety of tasks but we can still break them down to something that reveals if work has value or not.

As the work starts to get broken down it becomes clear that there are more development options than we could see at the higher level of breakdown. We can also see that by breaking work down further than normal we can add in tasks that allow us to understand value better.

In point 3 below therefore we have included a task for the FLOW owner to categorise questions and run through scenarios for different outcomes.

In creating this short list we have gone back and fore adding tasks, seeing if they add to the mix, crossing tasks out, asking questions and so on. What comes out of this is a new level of transparency. By truly understanding what we are doing we force work out into the open; we know what each of us is doing and nobody can disappear for a fortnight on a project that adds no value.

  1. As a FLOW owner I need to devise major class of questions that the work will answer over time such as:

    1. From the perspective of a distributor what are the benefits of current servicing scheduling arrangements? If we can answer this question we can seek ways to increase value at the distributorship while improving service to the customer.

    2. From the perspective of the customer: What are the issues relating to comfort in dealing with distributorships? We are assuming there are social reasons as well as economic ones for customer churn.

    3. From the perspective of the customer: What are the issues relating to timing and scheduling?

    4. From the perspective of developers what are the major task areas?

    5. From the perspective of the system owner what system architecture implications arise as a result of changes to a process

  2. As the FLOW owner I want to organise consensus on the desired outcomes of an online survey and a narrative survey at locations

  3. As the FLOW owner I need a draft list of questions to ask service customers in an online survey

    1. I need to devise categories for the questions and describe potential outcomes that the answers will yield

    2. I need to organise a standup to socialise the draft

  4. As an analyst I need to choose a survey tool

  5. As an analyst I need to convert the draft into a survey

  6. As an analyst I need to pilot the survey

  7. As a FLOW owner I need an evaluation of instant communications for the survey: Twitter, WhatsApp etc

    1. As an analyst I need to research previous experience of the the use of these tools for surveys

  8. As a developer I need to create a graphical account of the customers’ journey through the survey

    1. As a customer I need an incentive to to go to a landing page

    2. As a customer I need to arrive at a landing page

    3. As a customer I want a reward system for completing a survey

    4. As a customer I want to see a progress bar as I am completing a survey

    5. etc

  9. As an analyst I need a choice of survey databases

    1. I need a method for automating the analytics

    2. I need a design for feeding data into a survey database

  10. As a team we need to review the survey questions and the logic of the analytics

  11. As a marketer I need a draft narrative survey for interaction with customers at concessions

  12. As a marketer I attend a nearby distributor and talk with five customers arriving for servicing to test the narrative survey

  13. As a developer I need to describe a self-service scheduling app for distributorships

  14. As a developer I need to evaluate existing self-service scheduling apps

  15. As an analyst I need to evaluate: from the perspective of a taxi app-platform what would be the benefits of allowing us a brand opportunity on their app?

You can see that some of these are clear tasks being described here and there are questions that probably need breaking down further so that they can be understood as tasks.

That process is iterative. And some questions or tasks might be completed in much less time than two days. If the task is on a wall somebody might already know the answer, say, to the right analytics for this task.

The point of Flow at this stage is to keep figuring out the smallest unit of work. When you know those, you know more about resource allocation and estimating

.

Part of the activity turns to understanding and articulating dependencies between the units of work and any risks and issues that might arise.

Phase 5. Deliver, test and iterate.

Traditionally it’s a long way from these ideas to being in a position to stream work into the continuous delivery flow. But what if it were only a month? Or maybe shorter?

If we are set up for continuous delivery then our objective has to be how we can get customers to decide what has value for them. Too much prevarication on our part excludes customers from the decision process. We want to push things into a test environment as soon as possible.

To understand how that happens in FLOW, assume that you no longer have collisions as the work from different teams comes together for integration; assume also that your social environment is weeding out non-valuable work as you go. You are now in a position to push good work to customers to see how your ideas are received. And you can do that through A/B testing or any other analytical suite you choose. The objective is to learn quickly where the value is added and where value is still blocked. In the book we point out the options you have to monitor call centre activity and social media to create the feedback loops that will give you:

  1. Input into the KanBan tasks so you can correct what looks wrong

  2. Input into strategy setting so that you can learn more about what’s on-trend with your customers.

Summary

Value is something we have to learn to seek out at a variety of places within work and in the life cycle of service development. Yes, there is a statement called a value proposition but even this is iterative.

In FLOW we think of value-seeking rather than value propositions. We seek value in a number of ways:

In a Statement of Proposed Value we can hypothesise what we think will create value, assuming we can deliver on the promises of our projects.

In breaking work down we seek out tasks that have value and dump what does not.

We engineer projects so that feedback loops are constantly creating information for strategists and KanBan teams

We periodically conduct FLOW Optimisation Analyses to check whether the systems, routines or services we’ve created continue to add value.

You can argue that the value proposition remains more important than these activities because it tries to tie your offer to a customer need. That’s misleading, however.

Every time you look at your activities and ask questions about value you are providing more value to customers, either in the way you work, the opportunities to provide more and speed of adaptability or responsiveness. In all cases you can convey that to customers too. Being a company that relentlessly seeks value for customers is a highly impressive credential.

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