What is an IoT ecosystem and how does it work?

Internet of Things devices work better together, the more IoT devices that link up the better. So which devices and which apps should yours connect to?

Natural ecosystems can tell us ideas for building Internet of Things ecosystems

In the Internet of Things (IoT), the more devices that connect with each other then the more perspectives and capabilities there are to be shared. More data from different sensors and data suppliers; and more ways to change the real world. Like operating cars, home appliances and other machines or getting really useful options from screens or bots.

If you are a device manufacture or an app developer the problem then is: which devices and apps should yours connect to? If you can potentially link to any device and any app then which are most appropriate?

How do you avoid confusing your users when they use your product? How do you avoid confusing yourself? What to connect to is not a problem for the user. The device manufacture or the app developer needs to figure this one out. Just give users a simple list of high quality options that are personalised to their current situation.

Your product cannot link to every other device on the Internet. So which devices have the most useful perspectives and capabilities? You need a strategy that helps your product to be better at its purpose.

And don’t forget security.

Next, having chosen which other potential devices or apps should work with your product you then need to persuade their makers to partner with you. There might be an API to help you connect but close data sharing and brand associations needs discussions and agreements. And that means you need to get noticed, get taken seriously and get a mutually beneficial deal.

The prize is that the first products to build up their IoT ecosystem of partners will get more data and features to build into better services. As my son knows very well, a bigger and more varied pile of Lego bricks means he can build a more interesting spaceship or a more secretive secret base.

There is a lot of talk about business ecosystems and an ecosystem of IoT devices is a lovely thought in principle, but what actually is it and how do you build one? Looking at natural ecosystems might help us.

Natural ecosystems are glued together by ‘nutrient pathways’

The glue that binds together natural ecosystems, like rain forests, deserts and even a single puddle of water is their nutrient pathways.

What we think of as natural ecosystems are actually the ‘pathways’ that recycle scarce resources. The essence of natural ecosystems are nutrient flows along pathways which are based on the natural activities of many different organisms.

Whatever the ecosystem, the quality that makes a natural ecosystem stand out; the thing that makes people say ‘that collection of organisms and stuff is an ecosystem’ is how it moves resources around itself. Microbes, insects, larger animals and plants and other living things move resources around just by living their lives.

The animals, plants and other organisms can come and go, die off or just move to another ecosystem. The pathways need not be dependent any particular organism or even a single species. But the thing that makes an ecosystem appear to us as an ecosystem is the way it recycles scarce resources.

For example, rain forests actually have relatively few nutrients, the soils are very poor. When leaves fall to the ground they are broken up by tiny organisms. Then the nutrients are absorbed by fungi and quickly recycled back into the trees by their roots.

Recycling and reusing nutrients along specific pathways is what makes one natural ecosystem different to another. Different organisms have different ‘roles’ in the pathways and each role might be performed by several different species.

Business ecosystem pathways glue together the IoT ecosystem

If pathways that recycle scarce resources are the essence of ecosystems then what are the scarce resources that business ecosystems can recycle?

The scarcest resource for most businesses is customer knowledge. Customer knowledge about the situation any individual customer is in at the exact moment when they use your product; and knowledge about how all customers have used the product in different ways and in different situations.

Knowing the situation which an individual customer is in as they are using the product enables the product to be more responsive to the customer. And it enables the customer to get better advice and suggestions for using the product.

Learning about how all customers have used the product in different ways and in different situations helps a firm to improve the design of the product with software upgrades or with hardware redesigns. Or it helps to suggest solutions to common problems that customers find as they use the product. These solutions can even be suggested to customers by the product itself.

For example, Sat Navs make travel route suggestions and cooking apps make recipe suggestions. Knowing more about the bigger picture of the users life – the reason for the journey or the reason for the meal – would suggest more personalised options. Knowing what other users have chosen in similar situations would help generate more options as well as a more accurate link between a suggested option and a given situation.

This sort of information was scarce before devices connected to the Internet because the direct relationship with users was mainly with retailers rather than product manufacturers. Also, an Internet connection enables products to record how they are used and then to send this information back to their manufacturer.

Product usage information can be combined with information from different products and other information about users’ lives. A deep understanding of the wider situation that a product is used in helps it to be used more successfully.

The IoT technology stack is a good way of explaining how smart products can connect up and share data. But how do you build ecosystem’s pathways?

Building an IoT ecosystem by choosing devices to partner with

To start building your ecosystem, first ask ‘What customer knowledge do you need to make using your product more successful as it is used and also as you design and (re)design your Minimum Viable Product?’ Do this for every stage of your users’ journeys.

Next you need to choose the data suppliers who can share the data you need to manufacture this customer knowledge. The data suppliers who you partner with (the devices, apps and other sources) will be the components of your ecosystem pathways. The order in which they work together is the flow plan of the pathways.

And how do you persuade them to do it? Just explain to them how it all works using the logic behind your flow plan of ecosystem pathways. Your flow plan describes how each device or app plays its small part in the wider scheme of your ecosystem’s work just by doing its job.

Each device or app has a job to do, its role.  So your flow plan of ecosystem pathways is also the business model of why your new ecosystem will work.

 

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My new Econsultancy post – How purchase intent data can help you understand the customer journey.

I’ve a new post on Econsultancy, the digital marketing blog. It’s from some research I’ve just done with Maybe*: How do millennial shoppers decide what to buy?

We’ve shone a light into the dark recesses of the customer journey. The earlier on along the shopper journey you go then the less you know. But earlier on is when you want to influence shoppers. You can read it here.

Privacy: Is there a missing third party in our emerging Big Data society? (new white paper)

Personal data can be used for great harm as well as for great good. The more that data is shared between organisations then the more value it can create.

But personal privacy is becoming more and more of an issue, although the way firms handle, share and reuse data is much too complicated for most individuals to be fully aware of or able to deal with if data is mishandled.

For the last year I’ve been running roundtables, interviewing experts and going to workshops to try to look for some answers to these problems. This white paper explains some findings so far.

Personal Big Data: Is there a missing third party in our emerging Big Data society?

 

Executive summary

New Big Data technologies are rapidly changing marketing, healthcare, government, financial services, retailers and whole supply chains.

We are rushing towards a ‘Big Data society’ that is using data analytics to more efficiently target resources and to deliver incredibly personalised user experiences. But the precise use of resources and the personalised delivery of services require access to deeply personal consumer data.

Personal data can be used for great harm as well as for great good. The more that data is shared between organisations then the more value it can create – and the more difficult it is to control who uses it and what they use it for.

The change in how organisations use our personal data is happening whether we like it or not and we risk destroying trust if consumers are harmed or even surprised, by how their personal data is used. We need consumers to trust how their data is used or they will be slower to engage by sharing their data. This will delay the benefits of a Big Data society and leave the UK to be potentially overtaken by other countries with a different view of the importance of consumer trust.

But current systems of legislation and regulation are based on older technologies and ways of working that did not include cheap access to mass data sharing capabilities and personalised data analysis in real-time.

Our investigation incorporates the views of experts from regulators, government, commercial data firms and consumer privacy organisations. It concludes that there are several missing roles in our emerging Big Data society – a missing ‘Third Party’.

This ‘Third Party’ would support individual consumers to deal with networks of large and small firms; help firms to share and use data in new ways in return for doing so appropriately; aid regulators to bridge the gap between the market and individual consumers, staff and firms; and give privacy and consumer organisations a platform to help more consumers and to engage with more firms.

We propose a solution, a design for a ‘Third Party’ that engages the attention and resources of the different stakeholders to watch and help each other. Firms would have a strong interest in behaving appropriately; and in turn they would encourage their staff to behave appropriately and become more successful in the process.

Here is the full white paper: Personal Big Data white paper 3.0.

My new Econsultancy post – Why it’s always good to share in our Big Data society

I did a new post on Econsultancy, the digital marketing blog. It’s about the opportunities and dangers of sharing customer data.

Sharing lets us use our resources much more precisely and produce completely new services. But misusing customer data risks destroying customer trust.

Still, we all need that missing piece of the Big Data puzzle, so we all need to share more. You can read it here.

My new post on Econsultancy – Google Now: it’s about the data not the service

I recently did a post about Google Now on Econsultancy, the digital marketing blog. It’s about how Google Now is a great new service with its near psychic ability to make inferred suggestions.

But the real story is in how it gives Google a much much wider window onto users’ data than Search ever did. You can read it here.

Mobile Big Data: how to link very large scale analytics with very small scale personal needs.

Finger of God

[Source: Wikimedia Commons]

Retail is being drastically changed by new digital technologies like Big Data analytics and the services that mobile smart phones can deliver. Big Data has been discussed a lot but there is little analysis on what it can specifically do for firms and their customers.

Also, apps that run on Mobile devices, like smart phones and tablets are revolutionizing multi-channel retailing and customer relationship management. But mobile apps are usually just catalogues and directories when they could be personal shopping ‘sat navs’like your best friend owned the store.

Most pressingly of all, there is very little useful thinking, or practical advice, available on the overlap between Big Data analytics and personalised services that are delivered by your phone, i.e. the links between the outputs of very large scale analytics and the very small scale personal needs of individuals.

Firms are still working out what they can do with these technologies. Customers are still deciding how they want to use them.

We need a roadmap

New digital technologies are producing a bewildering number of options: new shopping and customer relationship technologies, new Big Data information resources, new analytical possibilities and new business strategies.

Firms need an underlying roadmap for taking advantage of these new tools and resources as they unfold and develop. We need to connect back to the fundamental business objectives of commercial success and amazing customer service in the face of a chaotic digital landscape.

This is the first of three linked posts that show the significance of these technology-driven changes; explain the underlying processes at work; point out the business challenges on the horizon; and map out the strategic options that are now possible for retailers, their customers and the brands that they partner with.

Part One covers how new Big Data and mobile technologies are changing marketing, retail and the rest of business from a business strategy perspective rather than from a technological perspective.

Part Two maps out and explains the confusing new options and approaches that these new digital technologies are now making possible. From the retailer’s perspective, from the customer’s perspective and from a business strategy perspective.

Part Three explains some ideas on how to deal with the emerging possibilities described in the first two parts – from a strategic and analytical perspective, then from an implementation perspective and then with a consideration of how these fascinating changes will continue to unfold.

Part One: A mobile app is like the finger of God

Mobile apps are location-here, segment-of-one, stage-of-now, and downloaded by YOU.

Every app can potentially give you incredibly personalised recommendations, suggestions and advice based on knowing where you are, who you are, being with you every minute of the day and being trusted by you (you downloaded it).

These dimensions are revolutionising how firms communicate with you, learn about you and produce services for you. Everyone you know and most people that you don’t know also has a phone so you could multiply the previous sentence’s possibilities by most of the human population.

But neither firms nor consumers have fully worked out how to use these dimensions. Using mobile phones to figure out a person’s location has grabbed a lot of headlines and initiated a few start-ups and service features like geofencing.

Services that run on smart phones naturally segment customer populations down to a single individual because we rarely share our phones. So phones are platforms for personalisation, i.e. precise learning about individual needs as well as giving customised advice and information.

Also, we carry our phones around everywhere and a lot of people never switch them off – so services can potentially be real-time and anytime, whenever customers need them. Most importantly of all, customers choose to download the app and then give the app the permissions it needs to work.

So services that are delivered by phone apps [or mobile sites] have the capability for complete personalisation in terms of ‘where’, ‘who’ and ‘when’ plus they are a potential bridge for two-way exchange of information.

What goes around comes around

Complete ‘who’, ‘when’ and ‘where’ personalisation is great but an app [and the huge supply chain behind it] needs to know which service options, product variants, SKU number, model, user experience configuration or other permutation of what it could potentially provide is best for each particular ‘who’, ‘when’ and ‘where’ customer at the moment that they tap the screen to say they want it.

This need to decide which service would best fit the immediate needs of a specific consumer will be even more pressing when apps suggests useful things without an actual request from the consumer. Like Google Now is starting to do.

The absolute best thing about mobile phone apps and services is not their in-build sense of ‘who’, ‘when’ and ‘where’ – it’s the information that the consumer gives to the app owner or service provider [and the huge supply chain behind it] plus the permissions to use it.

Mobile apps are not just a bridge to God-like services – they are a two-way bridge to God-like services.

‘God-like’ means not quite omniscient, i.e. you have to give the app some clues as to what you need from it.  Mobile apps know who you are [you registered], when you ask for something or contextually might need something [they are always on] and where you are [they are in your pocket]. So if the app does not abuse the data permissions that you give it [an unresolved issue] and keeps being indispensible then it can potentially act as the ultimate loyalty card.

Introducing the ultimate loyalty card – the Mobile + Big Data version

Big Data is the minute-to-minute personal diary of everyone and everything. Mobile apps have the potential to be the pen that writes your Big Data diary.

All our on-line transactions, communications and surfings are recorded and increasingly stored, analysed and used. But there are still vast gaps in our personal Big Data diaries. For example, a huge retailer like Tesco with a tremendously sophisticated loyalty programme, like Clubcard, only directly knows about the part of your life that is your shopping-life. It can buy-in shared data from its partners to get a better insight into your specific needs. But it can never know your full Big Data diary.

But a mobile app [or collection of apps and mobile services] – that you trust enough to give the right permissions to about collecting your personal data and that you interact with as you go through your life events – could potentially know your whole Big Data diary. The Big Data diary of your on-going minute-to-minute life.

Just think of how helpful [or dangerous] this could be. Just think of the services, new services and benefits to society that this could be the platform for. Nobody could accuse those people behind Siri and Google Now of aiming too low.

Linking smart phones and Big Data means everything in the cloud delivered to you, right here and now. The intimacy, immediacy and relevance of smart phone apps is combining with the vast scale and power of Big Data and the cloud.

This generates many confusing and unfolding possibilities. A massive aggregation of information and other resources is combining with a highly specific understanding of customised requirements. Very large scale Business Intelligence is colliding with very small scale human needs.

The scale and variety of Mobile Big Data is both an enabler and a barrier. For firms and government it changes the problem from ‘we would like to do’ to ‘which should we do?’ plus ‘are we sure that’s the best thing we could do?’ There are too many new possibilities in too many new areas.

Part Two maps out and explains the confusing new options and approaches that Mobile + Big Data is now making possible. It does this from the retailer’s perspective, from the customer’s perspective and from a business strategy perspective.

The flipside of the personal data coin: useful suggestions on one side and ownership, control and responsibility on the other

Think about how Tesco Clubcard and many other firms are finding out more and more of our needs, interests and other personal data – in fact every time we use a phone or a web browser to make a transaction or to communicate with friends we generate data that firms collect and can then analyse. These are the firms that we buy things from or that we ask for information to help us buy things. Or they are the firms whose services help us in other ways.

Whatever you do online generates data – when you search, when you click through web sites, when you register for information or when you ask questions you are generating data for those firms that are able to see what you are doing. Your broadband supplier, your web browser supplier and the owners of the web sites that you visit all know what you do because it is their service that helps you do it.

Firms can also get very detailed location information and timing information – especially when you use your phone for browsing or on the web. And that’s great when they use it for suggesting really useful things that you would never have thought of – like Amazon’s ‘People who bought these books also bought these’.

But what happens when firms lose your data or when they get hacked? (And many will) So how can you be protected? What happens when you say ‘its my data, I want to control how it is used!’ And what about sharing the value that this data generates with the person it is about, i.e. me?

So, on one side of the coin there’s the increasingly detailed personal information (Interests, Location, Time) that firms can use to help people a lot and create immense value. But on the other side of the coin there are unresolved issues of control, share of value and fixing damage when its lost or stolen. This general lack of clarity about control, value and fixing damage also means that the role of the regulators is also unclear because these issues are what the regulators’ roles are based on.

I think I have a solution to most of the problem of fixing damage, and the control problem, but I’d be interested to hear of any ideas that help with the share of value problem. I know how to create it, read my blog posts, but sharing value is different.

For example, what if I buy tomatoes from Sainsbury’s and then Sainsbury’s sells data on my buying behaviour to its tomato supplier so as to help it produce ‘better’ tomatoes. Then what if the tomato supplier makes more profit from ‘better’ tomatoes, e.g. because they are more popular. Sainsbury’s might have a clever deal to get part of that value. Like a reduced price on he supplied tomatoes or a percentage of the tomato supplier’s increase in profit.

But how can I get part of that increased profit? Should I get part?

I’m looking for different ways to look at this issue and for some underlying logic to work out how to share the value that is created. Any suggestions?