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Exploitation as contradiction in ideality

2 really disparate examples of exploitation here, I will do a couple of illustrations for defining these contexts as contradictions in players’ ideality and then applying a trend.

One from the affordable internet efforts and why even with reducing capex and opex telecom companies would not cut prices to customers and continue to exploit.

Player Function Ideality Contradiction and resulting exploitation
ISP/Carrier/Operator connect subscribers                          to internet not lose subscriber base, increasing revenues/cash flows, decreasing spend, monopoly increasing average revenue and profit per user directly contradicts with customers ideality to pay
Customer/Subscriber connect to internet for access to services and information pay nothing for connectivity, highest speed possible, always connected ties with devices, price increasing data plans, speed limitations, and forced congestion from operators
Investor invest for returns in companies that make profits reducing capex and opex with increasing revenues and profit is approaching ideality reduced customer service levels and migration of customers, puts revenue and profits on a decline, hence the stock value as well
Media Industry create and distribute media monopoly for content and affiliated business, no other competitive media / distribution channels becomes viable Access to media from internet directly contradicts with their business model to sell content from traditional forms of discs, cable tv content

Second example is around immigration from the recent Syria crisis, even though legal immigrants add value to the migrated place, why politicians continue to exploit voting population by fueling negative perceptions around immigration. But still continuing to turn a blind eye on labor exploits of immigrants to continue with a not so competitive economy.

Player Function Ideality Contradiction and resulting exploitation
State/Politician development and upholding state  sovereignty zero dollars spent on regulation, and citizens get all priority services from government, and never lose an election allowing cheap immigrant labor into non-subsidized industries maintains a bad economy building a false perception around immigration maintains status quo and votes from conservative population that wants to maintain sovereignty
Immigrant Labor to industry every border is open, every country is ‘migration’ worthy, on par with citizen benefits, rights protected lack of labor law to govern their employment means giving away rights, without votes or rights deprived of having a voice in the country
Industry/Employer Value creation for economy, investor, and customers cheap and exploitable labor use and less than minimum working conditions for higher profits, no litigation on violations lack of labor inspection / governance maintains  status quo, including less than worthy labor conditions and pay to immigrants and this as the only way to maintain competitiveness in a falling economy
Citizen Tax payer and uses benefits from state.Also customer for industry. Subsidized sectors, and unemployment benefits for citizens, Pay/Benefits without job. Subsidy perceived as right and any state capital spent on immigrants is actually something the citizen could be deemed eligible for as lost/wasted.
Border Control Regulate migrant flow into state no immigration (legal / illegal) means no patrol or control necessary migrants posing threats to sovereignty, and citizen welfare, calls for massive spend in border control and leading to a back passage creation

Now in both cases at super system level, you could add regulations that will move some functions from the players to another neutral authority. So Regulatory Authority could standardize price plans, open up migrations across, just like they do in insurance policy terms and conditions. Similarly new technology like unlimited connectivity say from Google Moon or, open id, could turn functions in favor of customers/migrants, while skewing for specific types of businesses and not the legacy ones.

In both cases simple system completeness trend will show deficiencies in the governance bit, and a massive undercut of benefits from customers/migrants as a driving force for the functions delivered.

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What is the system in the middle of 9 windows?

System Operator aka 9 windows is very popular in TRIZ tools specifically for problem definition and trending. I always had trouble in finding what is the system in the middle that we are talking about. I think I got the block primarily from the example that was used to teach 9 windows many years ago which had a ‘tree’ in the middle and all sorts of super system, past and future imaginations written around it.

  • But is ‘tree’ a system?
  • and can I put anything in the middle and construct the rest of the eight windows?
super system future
system present
 sub system  past

It just did not feel right to imagine it that way even if it did remove some psychological inertia, and helped you imagine stuff by space/time boxing yourself. To go further and beyond how you are applying 9 windows, I will introduce 2 useful concepts that will help you figure what this system is

  1. Tool/Product: Tool, in order to deliver the most useful function, changes the state of a product and can contain elements.
  2. Most Useful Function: Primary utility that gives a human purpose to the tool and product

One of the better examples I have historically used is “Withdrawing money from an ATM”. Both the tool and function are clear and it is worthwhile putting it in the center. Building on further, you can easily identify both what is inside the ATM and around it quickly, again identifying each elements’ function and operating zone in space and time.

ARIZ goes another level deeper to template the definition, as below “The technical system for __utility__ includes __elements__. Tool directly interacts with the product and products need to be changing its state (e.g. processed)”

It is easy to put yourself, your company, a really complex system architecture, vague frameworks and the like in the middle of the 9 windows, but really it will not help much in your innovation effort.

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Return of what in the world is triz?

When I made case for systematic innovation in consulting, I did not recommend any specific method set. The one that I am trained and have practiced is called TRIZ (aka TIPS/Theory of Inventive Problem Solving). Its basis is patents, it provides many methods to define a problem, find and resolve any of the 39 parameters trade offs / contradictions with 40 principles, recommend solutions for standard problems from its 76 solution portfolio, predict product/system from its 8 evolution trends. All the good things. From trizindia.org we have chatted on beginner questions to Dr Ellen Domb one of the few articulate world leaders in TRIZ based innovation as a podcast in 2 parts (Part 1 and part 2).

But it all comes with a few catches, if you cannot get the language of TRIZ, you cannot apply easily, if you do not apply you cannot learn, and if you never learn, you are always running short on good ideas. So really the facilitator’s role in TRIZ first is demystify, handhold in using the methods, never give out an idea even as an example, and mostly be silent, listen and ask questions. If the method is so systematic can I not get a machine to do all this in a flow, certainly possible and that route has been taken up by a few researchers.

As a leader it is necessary to make that time for your team to learn. And once that happens, some test the waters, some believe, some suspect, some ignore,

some really apply and when they do and get an idea that they never thought was possible beyond what was already told by the ‘resident genius’….. it starts to happen again and again.

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Trending innovation programs

TRIZ law of system completeness states simply that all systems needs an engine, transmission, tool and a control touching all the 3 to perform usefully. That is a heavy automobile metaphor to begin with and needs a translation to plain english and business. I will try to translate in stages, and then apply 2 other trends (again from the TRIZ portfolio) on the parts itself to see how we can forcefully evolve or design innovation programs.LawOfSystemCompleteness (1)

System Element
First translation
Second level translation to business
Engine source of raw power, muscle, energy Needs or wants in several spheres of customers, Investments that can give raw power ($, signals and time)
Transmission channel, deliver, route the energy Conveying need and investment to the tool which will actually create/generate solutions
Tool do the function, purposeful action, perform Performing the function ranging from solution generation, prototyping, testing solution, and finally delivering it to the customers
Control govern, command, supervise, moderate the parts above Governing all the above 3 through a system, process, or management structure

While we can recursively apply the completeness law to the parts also, it is not very useful for program design. So I will now go further with applying my 2 favorite trends

1. Transition to Super system and

2. Transition to micro-level.

System Element
Applying Transition to Micro level
Applying Transition to Super system
Needs or wants in several spheres of customers, Investments that can give raw power ($, signals and time)
  1. How can we find large number of small needs from the existing customer base?
  2. How can we make the investment size below a threshold (so no approval flows kick in)?
  3. How can we allow employee to invest in his own idea as money, time and effort?
  1.  Who is the customer’s customer, investor’s investor, director’s director, etc?
  2. Where are potential customers beyond who we are targeting now with the ideas?
  3. How can we translate external customer comments into needs? And those needs to demand?
Conveying need and investment to the tool which will actually create/generate solutions
  1. How can we convey needs from customers to large number of groups internally?
  2. How can our budgeting and investment management process allow money to flow into the small projects?
  3. How will customers test large number of potential solutions created from the small groups?
  1. How can we sell the value proposition of the idea for competition to invest?
  2. What are the need spheres of employees you can leverage like family, interests, networks, communities?
Performing the innovation function ranging from solution generation, prototyping, testing solution, and finally giving it to the customers
  1. How can time to prototype be reduced? 
  2. What ways exist to test the solution with many groups of users?
  3. How to deliver individual functions to many customers?
  4. How can we generate solutions that will need zero-minimal investments?
  1. What are the current start-ups with solutions already developed for the need?
  2. Are there academic interests around the need?
  3. Is there government funding available?
  4. How can we get from 1 large strategy to many small safe-fail experiments?
Governing all the above 3 through a system, process, or management structure
  1. Who all can be part of the governing structure?How can it be brought down to immediate reporting manager level?
  2. What processes need to be adaptive to allow small-scale governance?
  3. How can quarterly reporting be made bi-weekly reporting?
  4. How can data be collected automatically to report continuously?
  5. How can the steering committee be forced to look at large number of ideas?

 

 ….

It is now possible to look at different open innovation programs and see which trend became true and how their application is. May be in another post soon…

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Making case for systematic innovation in consulting

I am in the idea business for about 7 years now, usually my kitty is small in terms of budget to spend, management attention, and customer appetite to ideas. Problems/Opportunities are as always many and wide. Making this a green territory for the consultant in me. 3 realities that I face are pictured below. I will then pick reasons from each and make case for the consultant in you to learn a systematic innovation method this year. It is still not too late for a resolution.

First no one including you, your boss, his/her boss, their customer, his/her investor knows for sure which will be the greatest idea (since sliced bread, iPhone, facebook, flush toilet, the movable type, safety-pin, or whatever). Greatest here is one that gives max return, finds large customer base, impacts life, etc on the outcome side. So I go for safety with numbers, instead of the 2 large bets can I get 200 ideas and later ruthlessly eliminate, or make ideas robust socially from that base before investing. If I knew how to get from 2 to 200 ideas in say 4 hours.

Second, problems manifest as contradictions or trade offs. When I try to solve one problem I have only merely shifted its base to a different department, or another part of the system. Examples could be while increasing revenue there is a disproportionate increase in marketing costs as well, while scaling up operations fast there is also significant loss of critical substance/knowledge, by increasing hourly rates am I killing a customer account slowly, and more such combinations. I don’t want to compromise on anything really, we just yet don’t know how.

Third is on the search for the rare breed genius/creative person that all of us want in our team. My experience is hugely disappointing in this front, because I can never afford this “genius in residence” and wait for the eureka moment. Instead I take safety in history, all problems that can be solved, have already been solved (by all those dead geniuses I don’t have to pay for) and I just have to adapt the solutions for my situation. Again if only I knew how.

So in short here are the 3 different reasons why you need to add ‘systematic innovation’ to your consulting arsenal/portfolio,

  1. To take safety in large number of ideas
  2. To not compromise on outcomes or merely shift problems
  3. Not afford another unpredictable genius to solve problem that have been solved elsewhere

It does not matter much what that specific innovation method is, but Sensei is guaranteeing a sharper edge to you.

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Patterns in Leading Change

The idea of patterns is not new, but what is new is the methods and models for change that are now available that leverage patterns. Behavior and organizational change can now be effectively managed with these tools. I believe these will spawn variants in the consulting business (offered with the following adjectives superior, new, all new, refined, proven etc). Below are the originals that I learnt from.

Fearless change 

is a classic work, this book has a comprehensive collection of  patterns and methods to manage change, and it is very people centric. It is a worthy investment for any organization that is serious about making change be it *mm, km, innovation, 6 sigma, operational excellence or whatever.

Behavior Grid

from the BJ Fogg research base is another solid tool. I strongly recommend using the grid and methods or the easier wizard which I am sure is also a product of the applying persuasive tech.

behaviour grid captology.stanford.edu/

Here is my spin to the behavior grid specifically for innovation, change should be viewed as change in parameter. Green, blue, purple, grey and black are just ways in which a parameter can change. When the TRIZ contradiction matrix or another method set says parameter change, use the above as guideline for the real change.

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Evaluating Innovation

Evaluating innovation has always been a difficult job for innovators, investors, facilitators, and managers. With increased pace of developing ideas, it becomes critical to evaluate innovations effectively and quickly. Before I begin developing an innovation evaluation framework, I will define what I think is an innovation and draw some characteristics first. Innovations are

  • purposeful action and aligns with some personal or organizational vision
  • developing ideas that are perceived as new and valuable
  • impactful at a scale, may include financial, social, environmental, life impact
  • investments that may lead to disproportionate returns

Innovations are evaluated for various purposes like

  1. Qualifying for investment/grant/other resources
  2. Quantifying impact of the innovation
  3. Modifying the development process for a set of ideas
“While we recognize that the American economy is changing in fundamental ways- and that most of this change related directly to innovation-our understanding remains incomplete…centrality of the need to advance innovation measurement cannot be understated” – Carl Schramm in the committee report to Secretary of Commerce 2008

At level 0, I believe the following facets have to be considered

EvaluatingInnovationsL0

Evaluation includes the following phases/activities around data and reporting

1. Data Collection, depending on the kind of evaluation it may include quantitative and qualitative information.  Typically if data is collected from primary sources aka the field through surveys, direct interview, or secondary sources like agencies. Every collection effort should include independent variables, and dependent variables. It is useful to segregate between input variables, and outcome variables. Units of measure for all variables have to be standardized or they should be convertible. In case of comparison between different variables, you might want to consider some normalization process. Data quality standards are to be set prior to beginning the data collection and for any further analysis data has to be of some agreed minimum quality.

2. Analysis and Data representation, depending on the kind of data collected analysis methods will vary.  For example representations for financials will be in spread sheets and charts, social data will be on maps, stories will be as fitness landscapes. Typically here is where any hypothesis is provided, and tested, future state predictions like forecasts based on models are put forth. Comparison with history or benchmarks will happen at this stage as well.

3. Results of evaluation, should be an action or recommendation. In most cases evaluation leads to decisions by parties other than the evaluator. If this party is not identified prior to evaluation process, the effort is most likely to go waste.

“What are we really going to do with this? Why are we doing it? What purpose is it going to serve? How are we going to use this information?” This typically gets answered casually: “We are going to use the evaluation to improve the program” — without asking the more detailed questions: “What do we mean by improve the program? What aspects of the program are we trying to improve?” So a focus develops, driven by use.”  – Michael Quinn Patton

Once you have decided which facet of innovation you are trying to evaluate, we can now adopt from many of  available methods for doing the actual evaluation. I will try and list some of them below, with links to external resources that I have found useful.

Impact: EPSIS provides a detailed framework and clearly distinguishes between output, impact and performance and provides a set of indicators that can be used for direct measurements or indirect impact measurements. Social Impact evaluation on philanthropy from Stanford is a good place to start.

Investment: Investments related evaluation includes both input costs and outcome returns to compare innovations. For example we use something called as the t-shirt sizing for ideas at first level, that will give a scale estimate of cost. Return on Investment as a ratio is a good measure but the underlying assumptions for predicting returns has to clear, and the other common error is around data quality when predicting returns.

I personally use value investing check for fundamentals when getting into stocks, and the factors that are checked are around stability, margin of safety, and historical dividends. Investment evaluation should be reduce the impact of any failure and enhance experiment design. In many cases ‘closed world’ resources (freely available locally, and has potential use) play a significant role in reducing investment.

Diffusion: Interdisciplinary classic work in this field Diffusion of Innovations by E Rogers lists different ways and covers a broad range of research that has already happened in diffusion. I like the stages around innovation diffusion as awareness, persuasion, decision and implementation. Data collected should focus on units of adoption (individual, community, user groups, etc), rates of adoption over time, and other social aspects of the adoption.

Model: In this facet of evaluation we only focus on what model of development was used for generating and developing the innovation, and should cover business model elements and how each of the elements are being looked at. Data collection would typically include metrics (see size, time, interface and costs worksheet below from NUS below) on needs, stages of development, partner structure, productivity, etc. For example Villgro, kickstarter, and Google ventures all operate in distinct models for developing innovations.

stic time interface cost questions

Development: Entire field of Developmental Evaluation is dedicated to evaluating during innovation and applicable for complex, highly social, non-linear situations. McConnel foundation’s  practitioner guide is probably the best you can get for free.

I will cover a few methods for selecting innovation  like PUGH matrix, decision trees, possibly in another post. This will be my last post for the year 2012, and I hope to build on the momentum covering deeper and meaningful innovation topics in 2013. Happy new year…

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EMC Trends 2013 TRIZ overlay

As eleven EMC executives offer their predictions of which technologies and trends will transform cloud computing, Big Data and IT security the most in 2013, my aim is to find the underlying triz trend and possibly push one more evolution round. I assume a time frame of 1 year, basis is 8 TRIZ evolution trends applied to Mobile, applied on EMC executives predictions.

Prediction quote (emphasis and few links are mine)

My warped explanation of the underlying TRIZ trend

What can happen next on this trend

an intelligence-driven security model…will require multiple components including:  a thorough understanding of risk, the use of agile controls based on pattern recognition and predictive analytics, and the use of big data analytics to give context to vast streams of data from numerous sources to produce timely, actionable information

Law of completeness exemplified with the ENGINE understood as risks and risk related information originating across the board with a TRANSMISSION visualized as streams of information flowing to WORKING UNIT where actions are initiated from the information to contain risks and its effects and having some CONTROL on the above elements including analytics

Law of uneven development on above will mean the 4 elements will evolve in different speeds.

Within the same time frame, I feel the engine element will evolve the slowest with not many newer risk categories getting added but we may have to deal with geometrically higher number of information streams, with big data analytics playing a super system role. Governance at working unit level will go through changes as well with many tasks getting automated.

For CIOs, the common theme is “now.” Rapid time to value is the leading driver. In many cases today, the business unit holds the money and determines the priorities, but they don’t care much about platforms, just the best solution for a specific problem…movement to cloud solutions is only going to escalate

Transition to Micro Level will mean that instead of a single cloud solution at enterprise level, each department or project will begin its own adoption independently. Budgeting and allocation as always and the experiments and trials of solutions, both in size and time will shift to micro level. i.e. smaller projects with shorter time cycles to try. You can check the free trial offers from HP, Google, AWS, vmWare to see how micro this has actually become already.

Adoption rates will most likely be at the beginning of the sharp rise in the S curve (with X axis linear time, Y axis cumulative % of adoption of a cloud solution).

IT will begin its delayed policy making role later in the year with governance as the central goal after many micro-level cloud solutions get adopted in the enterprise.  Possibly negotiate with popular choice vendors for supporting internal laggard/late adopter needs.

The transformation to hybrid cloud environments, and the need to move data between corporate IT data centers and service providers, will accelerate. The concepts of both data and application mobility to enable organizations to move their virtual applications will become the norm.

Already the roles and responsibilities of the different channel entities are blurring. SIs are becoming resellers; resellers are becoming service providers; and even end users are becoming service providers. Over the next three years, it is probable that the traditional mix of end-user, channel, alliance and service organizations will change, merge or disappear.

Transition to Super system will mean aggregation and unification of the entire service procurement including licensing, integration, migration, channel management etc

More sub systems and services of the past will move to the super system and will be on the path to become ubiquitous.Most partner ecosystems these days already include license offers, marketing support, education support and account management for partners. Examples could be GoogleVMware partner programs

The emergence of the Hadoop data ecosystem has made cost-effective storage and processing of petabytes of data a reality.  Innovative organizations are leveraging these technologies to create an entire new class of real-time data-driven applications

IT will continue to see abstractions with more intelligence in the data center moving to a software control plane that uses Web-based technologies to access compute, networking, and storage resources as a whole (e.g. software-defined data center). Cloud model tenets like efficiency and agility will expand to include simplicity as data centers look for easier ways to consume technology.

Law of Conduction will mean emergence of standards for data and application portability this year.  de-facto standard is my expectation and de-jure standards especially from EU region is also possible as governments can step in to decide and declare norms from the “jungle of standards”

Law of Harmonization will necessitate smooth transitions at application and portfolio level and will mean newer services especially in migration and testing to make sure business continuity.

Simplicity, agility, portability testing, or <<other cloud tenet>> services may emerge as key sellers from offshore.

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Make more Money | Visualizing your Super System

I came to know of a colleague who started diversifying his source of income just by simply visualizing super system elements sequentially.

Super System Future  When he figured how to develop land into dwelling units this became a steady source of income as well. Most of his US based friends invest in real estate through him for development
System Present He then finds out he can actually train people and make some more money. When more people started coming to his trainings he found out creating a rental space for trainees is worth it as well, so he built paying guest accommodation for trainees
Sub System Past To begin with, he was earning a regular day job salary being a SAP consultant. He also learnt how to install SAP for training and implementation as part of the day job

An inspiring story, if you think about it, much can be attributed to forcefully thinking beyond the HERE and the NOW.

Also a great example of how a simple function of making money or value can be pushed to super levels over time using system operator.

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