Skip to main content

A data streaming platform to empower companies with intelligence through their entire business and value chains

Periodic Reporting for period 1 - ACTIVITY EXCHANGE (A data streaming platform to empower companies with intelligence through their entire business and value chains)

Reporting period: 2018-05-01 to 2018-08-31

Over the last months Activity Stream has conducted a feasibility study, performed with the support of H2020-EIC-SMEInst-2018-2020 (H2020-SMEInst-2018-2020-1. THe work included validation of the technical, commercial and financial feasibility of our innovation project.

Activity Stream's innovation is aimed at a huge business problem that is relevant to all industries: The complexity and high startup costs involved in implementing data analytics and intelligence.

In spite of the evident benefits of data analytics, most companies do not have the deep pockets nor the skills required to become data driven. First, they must collect data, clean, integrate and enrich the data, analyse it and then present relevant information to their users, preferably in real time. To do so is still extremely difficult for most companies. Moreover, dashboards developed in-house are commonly highly specific to certain types of data or tasks and are therefore rarely reusable. Data remains deeply fragmented and interoperability is low, even within tightly knit industries. Accordingly, data sharing and collaboration is still in its infancy. Data remains an underutilized resource and real time intelligence is only available to a select few, out of reach for most SMEs.

Our goal is to solve this problem, industry by industry. We are offering a turnkey intelligence solution with data exchange potential, designed to provide ecosystem support.

There is huge value potential for society in better and more responsible use of data. This value is realized differently in each industry, and therefore we focus on one industry in the start. The Live Entertainment and Sports industry is a part of the Experience Economy and is growing fast. We have confirmed the need by conducting interviews, looking at industry statistics and engaging in industry events. By helping the Live Entertainment and Sports industry become more effective in serving their customers and more efficient in their operations we will help them create value for society. Shared cultural or sports related experiences have been proven to increase social cohesion, inclusion and well-being.

Our objective is to roll-out our solution to thousands of users in the Live Entertainment and Sports sector and to start making it available for selected new industries over the next years.
We performed a technical analysis on the current platform, its scalability and robustness, security, and data governance procedures. We uncovered a few scalability issues that would have impeded our growth plans and data semantics issues that would have reduced our ability to reuse components across our customers. This work confirmed our industry-based approach, as use of data and semantics and they way employees use information can be very industry specific. Data semantics must be clearly understood and translated to a common language to enable reuse of analytics components and data collaboration and exchange. Presentation of information must be designed to support employees in their daily activities, freeing them from information overflow and time consuming data massaging.

We also did a commercial feasibility study, where we interviewed current users, future users, industry analysts and thought leaders. We have identified a clear market opportunity for our solution in the Live Entertainment and Sports sector. We face more competition in other sectors, but there is great interest in facilitating use of methods such as machine learning in all industries. Data collaboration and exchange is a blue ocean market. We have estimated market size and growth and quantified our potential. We refined our go to market strategy and pricing strategy and reviewed the key risks and mitigations. Finally, we predicted customer growth and calculated the revenue, costs and funding needs.
Our platform will reduce a great deal of manual work for employees, to begin with in the Live Entertainment and Sports sector. We estimate that showing revenue streams across different sales channels can relieve 1/2 day of work weekly in an average ticket selling venue. We are facilitating improved customer engagement through our customer moments. Loyal customers are extremely important to venues, where 3/4 customers commonly remain single item buyers. Theatres that have used data to understand their audiences have significantly improved loyalty and more and more customers return, even within the season.

We are on the verge of becoming one of the first companies to create a common data layer across an industry. This will greatly speed up analytics work and enable reuse of components, creating industry-wide value. Our platform business model is based on the principle that our customers will benefit from the enormous economies of scale and scope we stand to gain if our growth assumptions will hold.

Given that we will have over 2.000 customers in the EU by 2025 and modestly assuming that employees involved in data preparation are paid 20 EUR per hour, saving each customers only 1/2 day a week translates to almost 8 million EUR sindustry savings pr. year. The time saved can be used to create better content, achieve more inclusion and better experiences and get communities together in a real life experience.
High level approach