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Service Companies, Open Networks & the Global Data Supply Chain

Data is still the new currency. A few years ago I wrote a blog post about Open Networks and how that impacted the companies that produced consumer generated content (CGC)….

Data is still the new currency. A few years ago I wrote a blog post about Open Networks and how that impacted the companies that produced consumer generated content (CGC). Fast forward a few years and there are some new players in the data supply chain. Enter the service unicorns.

Service companies are ripping one out of the playbook of the data giants. A couple of new industry terms have created billion dollar service companies. 

Platform as a Service (PasS)

Sure, this was a model that was around but instead of stand alone data collectors like Twitter and Facebook, the goal is now to connect supply (human capital) with demand. The question gets asked, “how can we build a simple platform where people who have a service to offer can supply those who need the service, anytime they want?”

In a world where attention spans are short, people move fast and everyone wants to control their own lives, the gig economy at scale starts to take shape. Want to entertain? There is an app to help you become a performer. Want to make money driving people around in your car? There is an app for that. Are you a celebrity and want to give personalize responses to fans in exchange for money? You guessed it, a simple download.

At the end of all these apps is the platform. A logical application built to make it easy to live and work in the same space. The freedom to work when you want and get paid daily. The easier you make it, the more people will use it. The only thing you have to do is give the platform a little off the top and maybe a monthly subscription fee. At scale, this transactional model is very profitable.

A Reversal

The previous blog post talked about the goal is to be the source of data and sell the access to that data. In the service model, the goal is to flip this around and be the underlying service provider that connects supply and demand.

Data: Source > Supplier > Service Provider

applied to service organizations…

Service: Supply < Service Provider > Demand

Differentiators

In order to be a player in the bigger market, you still need to drive engagement with your apps. The main types of content that drive engagement are:

  • Content that resonates with a user’s purpose
  • Content that appeals to a user’s emotions
  • Content that fills a user’s needs

This is mainly done through personalization. Interestingly enough, personalization is rarely ever specific to a person. At scale, it’s just not feasible or cost effective. Personalization at scale is usually done through look-a-like segmentation. Given a set number of characteristics, you are grouped with people just like you. Based on historical patterns of behavior, you can confidently predict, or more importantly, influence behavior. The more data that is collected, the stronger the confidence.

For a service company, there are 2 new powerful components to add the list of differentiators:

  • Social reputation within peer network
  • Ease of app integration into daily life (doesn’t interfere with normal schedule or behavior)

Open Networks

You still need to understand what an open network allows to understand the value of such a network. With a service company, your integration points should be plentiful until you have monopolized the marketplace. The easier you make your services available to the market, the more adoption you get.

Why build an app if you can let others build hundreds or thousands of apps on your platform?

Ease of Access (Network Accessibility)

The most important piece of building an open service network is continuously generating new ways to connect and use the platform. Ive said it before, analytics are a drug. Once you have it, and you start making smarter decisions based on it, you crave more. You can never get enough. Companies more often are now taking a data-first approach to technology and that is smart, and required to scale quickly.

Contribution leads to lower cost of ingestion

If you are growing the network, you should be willing to accept the value of supply in comparison to just a product revenue model. The more a person (or thing) contributes value back into the network, the less it should cost for them to pull data out. It is a typical process on getting supply to consistently contribute to demand.

The health of an open service network is determined by the availability of supply.

Analytics

Just like in data platforms, the validation of network usage depends on consistent analytics. You have to strike the right balance between the availability of supply and the demand for the service. This might mean taking a hit up front while you are gathering data to support more effective marketing and process rules. Once you realize the value of the supply and what people will pay for use (anonymous, raw and usage metrics), generating the right profit model is easier. Having data to support iterative evolution and service offerings is key.

Securing data

Privacy and security is essential to success. Protecting user and supplier data has become even more of a daily task. The service network should be simple and limited in access points, the only contradiction is your app service layer. Provide secure, reliable connection points and your service will spread like wildfire. As you build teams to support these goals, treat yourself like a vendor and security will be a much easier task.

Global Service Supply Chain

Find a service industry that is full of connectivity challenges, bridge those with technology then you have the makings of a unicorn. Service workers should not be pitted against each other, they are part of an ecosystem that should work together to build more and more ingestion points. The control is put back in the hands of those on the front lines. Consumers still want things faster, but the patience of waiting has gone away. The market expects immediate solutions and companies that can scale those solutions and recognize those patterns of behavior give way to new predictive models, interpretive features and more access to supply.