Prosumer engagement will replace Consumer business models (Utilities)

I had some very recent discussions about the new emerging business models, based on storage. Storage will totally change the way we approach consumption and will create new models and services around it.

In my view storage will bring a big revolution into the smart grid space/utility market, identical to the one that RAM (Random Access Memory) brought in the Computer Architecture, back in 70’s. The ability to store and manage capacity in an optimal way, is a great advantage to any multi-variable system (Electricity, Fluid Mechanics, Logistics, Sales, etc)

Storage will give great power to the local users ie. Prosumers (energy producers and consumers at the same time) and various business models will be deployed around them. Still, many moving business parts are around and still Utilities, DSOs and Regulators are trying to position themselves, in terms of pricing, regulations, policies or even to take lead advantage of the first mover. Innovation and especially incremental innovation that has end-users inside, is the one that pushes things forward. And especially in a traditional slow moving industry (utility) where a big digital transformation is about to begin (already present in some countries and local markets).

Prosumers will have power (business and data power, prosumers will own their personal digital data !) to manage/monitor/evaluate capacity and with the addition of current digital technologies (mobile apps, a bit of sharing economy, SaaS platforms, analytics, AI, IoT frameworks, etc) various disruptive business models will be tested. No-one knows exactly right now which one will be the dominant one and which will scale up fast. Pricing, tariffs, regulations, are somehow part of the strategic game and will be used by Utilities and DSOs to position themselves.

A big questions is WHO owns storage ? 1) the consumer ? is it really educated and engaged to use it thoroughly ? 2) The DSOs ? primarily for balancing and frequency regulation but this requires automatic control of the battery (or strong consumer commitment) and new financial models for subsidizing storage installations and 3) the utility ? for supporting new Prosumer DR and DMS functionalities (I call it Prosumer Demand Response -> PDR) and for load shifting… still many questions to be answered

However, the Prosumer will be in the middle (still Home automation has some years ahead). Will be the one that has to be engaged with the local “micro-grid” system and the one that could support some disruptive models. ie to sell its selected capacity on a “on demand” basis to EVs (neighbors) with a charger outside its house and a POS for online payments over Paypal; this can be supported with social apps and sharing platforms (storage marketplace). Of course pricing will be important and will depend on other prices for the grid.

Another model for the utilities would be the use of EVs as a leasing to the utility customers (Uber-like) and by getting credits (by charging the EV to specific spots based on the utility signals) to earn discounts in the home utility bill (provided that the user is a customer of the same utility). It happens that my company works on these specific scenarios (over game mechanics and consumer engagement in a larger sense) and still we think that innovation will pop up from these small human-oriented disruptions…these will push utilities to adopt things, new things…

Hence, Prosumer business models are an important part of the utility digital transformation process and the consumer will soon be a romantic definition in dictionaries. All we need is customer education, awareness and to drive the correct engagement to the correct target groups that will lead disruption (Pareto principle)

“Dark Data” & “Interactive Effects Theory” in Behavioral Science

 How engaged you are ?

In general there is a lot of discussion lately for the term “engagement”. What is actually the core difference with the term “loyalty” ? there are many articles defining the difference and some people point out that engagement is a metric of loyalty or engagement leads to loyalty… I kind of agree with most of them since they are related with revenues, product adoption, etc; however nobody puts the term human behavior in the centre of the whole macro-system: Human – Technology Interaction, HTI

To shape any user’s behavior using any modern digital service (app, online web, social, etc we live in the Digital Transformation era) initially some simple demographic and contextual data is required. However, if we want to approach engagement as it should be, we have to take the analysis one step further, and among the previous ones, we have to merge psychographics, sentiment, training and specific behavioral data that are not visible to the simple eye including their correlations

Basic queries to be answered are “Do users follow a particular pattern in the product/service ?”, “Why they are doing so ? ”, “What interaction they usually do ?”, “How results are determined by their initial actions and what exact actions are these ?” and “What is the impact of their behavior on simple daily actions they do”. In other words, accurate correlated behavioral data tells us not only what is happening, but also how and why it is happening.

Connecting the dots is the key, even with metrics that are not visible or measurable to the naked eye

Based on my research all these years, I refer here to two very important terms that we are lacking in almost all engagement/loyalty or customer experience reports and analytics procedures: Dark Data and Interactive Effects and of course the use of a complete Engagement Framework that will put all functions on a procedural map and orchestrate the whole system to follow the consumer journey, which is a multidimensional random variable


Dark Data

What I mean by the term Dark Data ?

Dark Data in Data and Behavioral Science are these KPIs/metrics or even raw data that are not easily measurable directly (via sensors or other devices) and they may exist only if we trigger the human system under specific conditions and for a small period of time

By using an app, I can analyse the clicks, pageviews and other directly measurable indices and derive patterns that will drive my UI, my app functionality or even understand my customer; however I cannot measure the “learning curve” or the “learning speed” of the specific user nor his sentimental reactions during his digital experience or what other friends are telling him that specific time about the digital service…not until I run a quiz, a test, a gamification approach, a survey or apply other innovations and analyze time responses, knowledge curves and other variables…this is Dark Data and they do play an essential role on human decision making that drives a part of engagement

Another example is to discriminate in a class the good students, in terms of grades and good behavior…I cannot measure that until I run a test and check if they will try to cheat…this is a wrong behavior that tells me a lot about his character but do not know until I trigger the system and do not relay only on the final grade

There are ways of measuring or creating on-the-fly additional data and metrics that tune the human behavioral model and reveal Dark Data…

so triggering the system, creating additional metrics and measuring dark data on a human-digital relation, drives better the engagement models


Interactive Effects Theory

A human behavior is comprised of actions and reactions. This can me modeled as a chain, or even better as a Markov Chain, where its state is only related to its previous state and in each state human can take only one decision. In modern behavioral science and engagement, we should analyze these Interactive Effects

For example, if I want to shift your energy behavior and make you save energy, then I could educate you and change your cooking habits. To do that, instead of sending you messages and tips, I could propose you a specific diet or I could offer food incentives that could shift your energy, by eating healthy food

This is an example of an interactive effect. To model that, you have to create a connected semantic model, identify the states (action, reaction, result), deploy a Markov chain with many parallel options and start playing with probabilities and then tune the model using the actual data you are getting from the digital service by following the human actions. We do that and it works !!


Engagement Framework

All the above points (and many more) should be on a unified map, should work together and should be correlated. Thus, we need a complete Engagement Framework, that will orchestrate the engagement analytics, the behavioral incentive models, the personalization, the dark data sensing, the interactive effects and drive actions and reactions on a timeline, in order to validate the engagement model and to achieve actual, measurable engagement metrics !


I will refer to all the above, I will explain how we use these secrets in our Utility Engagement Services with case results (some great numbers) from our DiG SaaS Engagement Platform ( in my upcoming talk about engagement and gamification at the European Utility Week 2015 in Vienna (

Join me there ! @


My 1st open Futurology talk @SAP forum 2015

In one of my recent articles about the Theory of the 5th Dimension, I referred to the digital “5th dimension” and how human physics will interact with the social cyberspace in real time; the key is wearable IoT sensors and integrated Social Cyber-Physical systems – CPS

New mathematics and methodologies will be derived and complex equations will be created to describe the digital-physical time-variant interaction over a huge multidimensional feed of various sensor data and correlations with human behaviors

More in my recent futurology presentation @ the SAP Forum 2015



Digital Transformation and the “virtual-physical” world on a 5th Dimension

In some recent discussions I had with friends, the term Digital Transformation (DT) came up. DT refers to the changes associated with the application of digital technology in all aspects of human society. And when we talk about humans this is where a second term enters into the equation: physical world.

Many big vendors refer to this term or have already developed services about transforming digitally old markets or the human society to jump on a higher digital dimension…

If we try to approach the topic from a different perspective, someone can admit that digital and social are becoming the 5th dimension in our life, if of course we accept that we experience all the other four (still without any control on the Time dimension)

Let me get it simple: when Facebook entered into our lives some years ago, a brand new virtual world was born that reminds a bit the super movie “Surrogates“. As this interactive digital human-driven subspace evolves, new technologies arise to make it more interactive and transform it to something more “human-oriented”;

Oculus buy-out from Facebook was not at all a random event, a new 5th dimension is under development, the one where we will be able to control all physical dimensions (our appearance, our status, our profile, our avatar, etc) PLUS time: a fully digital-virtual world with human-driven avatars and emotions. Looks like Matrix

The immediate need then, would be to connect somehow some physical variables from our real-life and upload them into the virtual world; and this is where Internet of Things -IoT- technologies will help to the maximum degree.

IoT still searches for its value proposition…his unique value prop as the technology is there and evolves fast. Various IoT sensors (wearable or not) that will collect emotions, physical interactions, medical data, health and other variables will be uploaded to our social/virtual profile and will start interacting with other virtual characters, forming a digital social world with interactions based on real data, multidimensional and not single-dimensional as Facebook right now

This is the Digital Transformation not of any industry but of the real human physical world, as we humans will be operating on a 5th dimension…the next step will be Transcendence, where a fully physical human model (descriptive data of our body, emotions, experience, memory, life interactions, psychometric, etc) will be digitally uploaded into the cyberspace…;-)

…more on this topic on my upcoming futurology talk @ the SAP Youth Forum pretty soon 🙂

Technology Transfer and TTOs

I recently read about Stanford’s SystemX, a way to create innovations and new products by linking University research and procedures with the real industry.

SystemX is organized around six focus areas. In each area, faculty and graduate students work with companies to explore ambitious innovations.

“This helps companies more easily identify Stanford faculty who are working on topics of interest,” Wong said. “That process used to happen by word of mouth, but SystemX formalizes the process of pairing companies with researchers.”

One of the big advantages of the US University system is the strong link with the industry and the local ecosystems, especially in the Bay Area, where SV companies arise every day. Other emerging Uni-Market ecosytems in US are in Austin TX, Boston MA, NYC NY and Seattle (…and more)

However, converting research into innovative product development is not an easy thing to do (I did that and its tough). Converting a PhD or a research output paper into a product, means that you also need to solve a problem in the market (apart from the product development), or at least predict the need and manipulate the solution behind science as a along-term approach.



The secret of what we call Technology Transfer is the word: correlation or combination. You need to combine the applied research outputs with the current technological level, identify that your execution is feasible and viable and check at the same time society’s maturity (for adoption) and timing (for scaling).

For me, the ability to identify recurring needs, combine and correlate various parts of technology and map them on the business and time dimensions, is the secret of modern entrepreneurship and innovation. All you need to do is to analyze and predict the market to be disrupted (timing).

But because the majority of the applied research and scientific work is being done in Universities or Research Institutes, this is where Technology Transfer Offices (TTO) enter into the model. TTOs help University students/researchers or Uni-be entrepreneurs that have good ideas during their University years, to approach the market and commercialize their idea or even produce IP (patents). The majority of them do not know the “lean startup model”, they have never written any business plans, sold products or services and never pitched to investors or potential clients (leads). Of course this is not their primary job; their actual job is to produce high quality research and publications (researchers) but if they have the ability to understand “basic business” the probability of achieving something or becoming entrepreneurs is even higher. One difficult thing to do is to actually understand the basic value proposition of a research output and optimally match it with a business opportunity or predict  this opportunity. This is tough and you need to be very well connected with the market and at the same time understand applied science.

Based on my experience, the key steps towards a successful TTO service (either in the Uni or as outsourced service to Research Institutes) are the following:

  1. Identify and map research papers or research outputs with market sectors and cluster them into business categories (ie. Analytics, Medical imaging, etc)
  2. Evaluate the innovation potential of these results and outputs (using the G/Score or other innovation assessment methods)
  3. Evaluate the business impact of the research outputs (tough !)
  4. Evaluate the technology potential and the ability to become prototype under the current technological status
  5. Optimally map these filtered and clustered research results with a problem of the market or the society and identify the execution potential (toughest !)
  6. Check society’s adaption rate (behavioral metrics, psychometrics, adoption criteria and social norms) and correct timing
  7. Map results and filtered research outputs from above with a good team to deploy and execute
  8. Move on with all initial business procedures (prototype, lean, customer feedback, etc)
  9. Apply Google Sprint method for product optimization
  10. In all the above, you need to have smart guys to execute all these steps…really hard to find; if these guys are Profs, even better as they can act also as angel investors (optimal model)

The above steps are difficult but necessary for a research-to-product transition. When this procedure is being followed by companies or big corporations (either using internal R&D or/and Open Innovation and external filtered sources) this is where the Chief Innovation Officer comes in with his “intrapreneurial” team and the most difficult part is to align corporate strategy, time and funding criteria/go-to-market.

To conclude, TTO services is another mutli-variable optimization problem that a human (CIO or researcher/entrepreneur/TTO) has to solve. And if this gifted guy can also predict these trends and guide applied research towards solutions and products, then we are talking about a “Futurologist”…my favorite ! 😉


Amid technological breakthroughs, companies and organizations are striving to get higher on the market’s ladder. In order to keep up, they have to make their customers loyal and engaged to their products and services. This need is amplified on the utility market, where it is not just that profits are high and potential loss of customers is critical, but also the necessity of engaging customers into sustainable behaviors is urgent. Thus, a tangible challenge emerges: How can utilities “nudge” their customers to shift their pro-environmental habits while maximizing their perceived value so as to “lock-in” them in the long term? Intelen’s answer is: Gamification.

Till now, multiple approaches to gamification have been piloted and commercially deployed within the energy sector.  Each leverages different gamification techniques and different core objectives. However, not all gamification recipes can lead to positive outcomes.

Take for example rewards, a core element of gamification. Most of gamified experiences rely on a system of external rewards that is restricted to points and badges. However, research reveals that such rewards have negative impact on users’ engagement. Since rewards and punishments are just two sides of the same coin, joy of the short term could be easily turned into disappointment and dissatisfaction if such elements are seen as incentives. Thus association between rewards and users’ activities should not to be taken lightly.

Intelen has developed such an expertise on gamification that can take engagement one step further. By incorporating points that are redeemable and can be translated into personalized prize as well as badges that are shared between peers or can be shared on social media, utilities customers’ long term interest, motivation, satisfaction and engagement, are ensured.

But Intelen does not stop there. Intelen also integrates in an optimal way other elements like peers’ ranking, levels and leaderboards, and mechanics such as short-term and well-defined goals, positive reinforcement, subtle feedback loops and features’ unlocking mechanism, so as to make sure that triggers directly user’s emotional level and deliver the maximum gamified experience.

At its core, Intelen’s gamification takes into account multiple learning theories that indicate evidence on motivating users perform sustainable behaviors. Among them, task based learning that assumes practice and action as essentials in order for a desired behaviour to be taught, subliminal learning that suggests knowledge to be acquired even in an unconscious way as well as social learning that implies people to learn not only from their own experiences (trials, errors), but also from other social models and other people (ex. family, friends, colleagues and people in the public eye).

Lastly, by utilizing granular and real-time energy data, Intelen provides instantaneous feedback on energy consumption and feed a recommendation system that reverts to users personalized tips on how to achieve energy efficiency and reduce their peak demand.

By turning energy management experience into a game, Intelen promises to deliver engagement boosting, loyalty and behavior changes associated to the inefficient skyrocketed energy consumption.


My interview on consumer engagement

Vassilis Nikolopoulos is CEO and co-founder of Intelen, Inc, a New York-based emerging startup focused on smart grid big data applications and energy analytics/engagement. I had a chance to catch up with him a few weeks ago at Greentech Media’s Grid Edge Live conference in San Diego. In part, I wanted to follow up on the interview he did back in April 2013 with Greentech Media President Rick Thompson, in which they discussed the networked grid and what Intelen does to optimize energy efficiency in buildings. That includes Intelen’s integrated engagement platform that combines data analytics with human behavior. In that interview, Nikolopoulos talks about Intelen’s dynamic approach to “gamifying” demand response using mobile applications and its engagement platform. Here, we talk about the “human element” of the energy efficiency equation, on the energy cloud and on how utilities will need to change their business models in this rapidly evolving market. Cross posted from Scaling Green.

Tigercomm Executive Vice President Mark Sokolove: Intelen recently released a white paper about optimizing not just technical approaches to managing and reducing energy consumption, but also about focusing in on the human element of the equation. Can you tell us a bit about Intelen’s work in better analyzing and mapping human behavior relating to building consumption?

Intelen CEO Vassilis Nikolopoulos: Sure.  One of the biggest challenges and problems in the engagement domain is how you actually measure engagement, because human behavior is something intangible. So we had to provide some way, we had to innovate in order to create a data-driven technology to measure the actual behavioral change and to see human engagement going on.  What we did was to create a unique data analytics platform: a combination of a dashboard, a learning management system and a mobile app that can act as an information and educational gateway in between the cloud platform and the humans. As we all know, smart phones can be considered as your digital extension to your behavior.

So what we did was to approach the engagement problem from a human perspective and not from a utility perspective. Right now, the definition of engagement is it’s something the utilities want.  Utilities want that because they just set up smart meters, so as soon as they understand the value of data and what lies beneath, they go and search for an optimized engagement mechanism to engage their customers. On the other side, we go in and approach the engagement problem from the customer’s side and not from the utility’s side.

So, we set out and we have analyzed,  after several years of continuous R&D, specific, permanent human needs that can sustain a continuous engagement philosophy and procedure. We built the so-called subliminal learning technique. What is this?  Based on our R&D, we found out that if we create training and educational material around an educational objective and we “gamify” the educational objectives, we can actually change human behavior.

How do we do this?  By offering training materials to users, to people, to students, to customers, based on their behavioral aspects. Let’s say that you want to change student behavior – to set up the thermostats in their dorms correctly, for instance.  We go and create educational material that can last 2-4 weeks, and we have as an educational objective to raise awareness on this specific topic by offering multiple-choice quizzes, tips, announcements and multimedia content, articles, videos, how-to guides,  and other educational features about how to correctly set up the thermostat. We offer videos, surveys, educational material you can use from your smart phone app. At the same time, we “gamify” the whole experience and we offer the possibility of prize incentives or social competitions.

Then, we go and we measure 5-6 important data-driven engagement metrics. We measure engagement. We measure efficiency. We measure participation, knowledge, commitment and influence. Those are metrics for which we have data from the mobile app, social networks, demographics, real-time energy data and our dashboard. Based on this combined data, we create data-driven human behavioral metrics.  So we know exactly how engaged you are with the platform, how efficient you are in switching the lights on and off, or how efficient you are in setting up the thermostat.

Of course, we measure the impact because we have the data monitoring platform that can be hooked up to smart meters. We have some great partnerships in this space, such as Obvius, where by using their advanced data loggers, we can track energy or water information to the second, and we can measure the immediate impact of our engagement. So, as soon as we engage you and offer you this material to change your human behavior, we can measure the impact to the actual building’s consumption. It’s like closing the loop.  First of all, we know how to engage people. We know how to quantify this engagement mechanism. We have the real-time Key Performance Indicators that actually measure the engagement and can actually measure also the result of this engagement to the actual daily consumption.