Often times investors look at the current investment opportunities and feel dread due to the complexity and rapidly evolving nature of business. In 20 short years the internet crawled its way into the bulky PC’s of Wall Street analysts and a few daring e-commerce entrepreneurs. Today the internet reaches far and wide, service virtualization is the standard and the motto is "if you are not refining your customer value proposition, there is almost certainly someone else who is".

Current studies estimate that less and less people can handle the increasing loads of information that are branching out. There needs to be support for decision makers, assistance for customer representatives and tools for engineers to ensure that their tasks are still relevant and their methods fall within the standard performance benchmark, or risk being disintermediated overnight.

It is easy to get sidetracked by all the new trends, articles and opinions surrounding big data. A simple internet search about data science can retrieve a incongruent list of facts and claims about disruptive business models, key success factors, measurements and value-adding activities, however there is rarely a moment of clarity or high-level comprehensibility. For this reason there is an explosion in the labor market of data scientists. The supply-demand statistics look grim due to large shortages of individuals capable of making sense of the next generation of business challenges. In short, data science is hot, hip and happening. It also brings up the perspective of why field of information technology is so popular and booming. The general take away for companies and everyday clients is that the main purpose of data science involves the provision of insights.

Real-time is too late

Insight into daily business operations is the starting point, but should not be the end-goal of analytics, rather the elucidation of facts that support decision-making. At Newest Industry,  we prime ourselves to the vision that no single individual can understand and hold every single piece of information in mind at all time. This approach opens up a dialog to data-driven decision making, deep-learning insights and real-time triggers for customized , just-in-time actions.

we prime ourselves to the vision that no single individual can understand and hold every single piece of information in mind at all time

Efforts have already been directed towards tackling the business challenges surrounding data at Newest Industries with projects such as Jumba.nl. In order to become a more present part of the users’ life, the company is tilting the market by establishing a long-term connection that grows and fosters communication between the end users and their properties. The property get a voice of its’ own with which the user can interact. Signals for the health of a household, or information surrounding the neighborhood or cultural trends are shown in such a way that the users can act upon the latest development surrounding their current or future homes.

Need for change

The current market is packed with many brokers who operate in a traditional business model. An agency is typically the focus of supply-and-demand and dictates the pace of a sale. This leaves end customers with little control or possibilities to challenge the behavior of their broker. This is where Jumba.nl shines! By making the entire process transparent and easily interpretable, our online platform allows a user to put his household up for sale in 15 minutes.

With the focus of having a user-centric platform, Jumba.nl differentiates itself from incumbent players that only provide access to their platform via a broker representative or expensive subscription fees. The real value-adding benefits arise when a user decides to put up a household for sale. Based on location, a variety of factors operate to determine self-generating context for the ad placement. From proximity to the points of interest throughout the city, to specially tailored interests from the visitors’ social media interests and likes, the context will seem alive and tailored to maximize the exposure to the most relevant items for our users.

Another meaningful component is a cost range estimate that calculates the likely value of a household, next to the demanded price. This service works based on the parameters that a user selects when updating data about their household. This is a reflection of average neighborhood household prices, the real-estate market condition or the foundation of the house. The entire algorithm within Jumba.nl is extensive and difficult to explain without diving into the technicalities of information retrieval systems and machine learning algorithms. The real added benefit is therefore the creation of the first independent digital agent that is integrated directly into the website.

There are good news for the agency representatives as well. As customers exercise more control over the process of acquiring or selling a household, it frees up time and experience for the representatives. New services such as intimate knowledge about an area or cultural and historical monuments, traditions or hobbies become an asset to help create more meaningful context and remain competitive. Another popular service trend with showcasing households is professional photography of the rooms and garden themselves. When displaying the property in this way, studies have shown a higher user engagement.

The main benefit of Digido can be conceptualized as a personalized interface that offers a marketplace-like environment where communities can form and interact

Changes are coming to the insurance markets as well. A challenging task by itself, administration of the many types of insurance packages, different suppliers and easily misinterpreted guidelines for claims have made tracking and accounting difficult and unappealing. With Digido, we are introducing a means by which to centralize all the disperse information an individual may have. We aim to provide an  overview of the multiple executive documents, which in turn allows users to better control the most important aspects of their financial filing system.

The main benefit of Digido can be conceptualized as a personalized interface that offers a marketplace-like environment where communities can form and interact. This could lead to services that directly involve the suppliers of insurance packages. Fostering communication will create a more competitive ecosystem of supply and demand, but also give rise to new types of financial products such as loyalty or group discounts, personal interests or association filtering and recommendations. The main differentiator here is that data about the users and their current insurance packages will give decision-making power. Drawing from larger groups, a variety of suppliers and in real-time can increase the most effective  way of selecting the best possible offers for a service, eliminating noise and reducing the time needed to manage personal administration.

There are exciting features to look forward to with Digido. Automatic content extraction and profile generation for new users is predicted to lower the barrier to entry. Moreover, quick scan tools regarding life insurance, retirement plans and unemployment support will give actionable triggers that again will be available to the users. The most relevant aspect of these is to use the various and complex data that individuals have in the form of generated summaries, tips and translations of ‘hidden’ meanings, into clear and transparent action points.

Data Science at Newest Industry

Data science practices are relatively new and still in development. This makes it challenging to understand exactly how  the best process or development cycle looks like. At Newest Industry, our team draws from various methodologies and applies the best practices in order to fit the current challenge at hand. Nevertheless there are a few guidelines and assumptions that hold true from project to project.

The epicycle of analysis | Roger D. Peng, 2015

Though there are many technicaltools available that each require different degrees of knowledge and skill, there is a generalized model for conducting analysis which is split into a 3-step iteration of a) setting expectations about a question or problem, b) researching if the solution to such a question has a particular set of characteristics such as: has not been answered before, is feasible, is built in a framework of trust and that it has 1 main interpretable answer, c) matching the expectations to the results of step 2. If everything is aligned then the cycle starts over, however on a different 'gear', else there needs to more communication between the management and analysts in order to 'sharpen' the question or goal.

The following illustration shows how this 3-step iteration can be applied at every process node that composes the data science project workflow.Keep in mind that although this high-level overview of data analysis is a good set of guidelines, there are other competing frameworks that are even more popular. For instance, the Cross Industry Process for Data Mining (or CRISP) follows an agile development cycle that shows a nonlinear path between components. However the 3-step process of setting expectations, collecting data and matching expectation with data is a common feature for both concepts since it sets the pace for the work flow, as well as gives a starting and orientation point for people working on the project, as well as outside stakeholders.

Data enrichment proces | © Newest Industry, 2015

Main value proposition

At Newest Industry we are very excited about all possibilities of web, mobile and data technologies, specifically the value adding services that these technologies can bring to consumers. Setting up a business around big data analytics implies positioning ourselves in a way that reflects our core goals and values into the products we bring to our customers. Sounds easy enough right?  

The starting point for every concept we create is a combination of innovative (web)technologies, modern user experience, with the end-goal of creating a set of digital productsthat unburden and support consumers. We believe that the majority of services do not have this pivot in place and therefore services are seldom created from a ‘customer-first’ perspective. And that is where data analytics comes in handy! Transparency and customer independency are key values that are integrated in all concepts that arise out of Newest Industry. Transparency is reached by clearly presenting combined open and closed data sources, enriching data and generating valuable decision making information that can actually help the consumer in decision making processes. Basically taking away information asymmetry and creating a more leveled playing field. That is what makes us so enthusiastic and excited  about data and analytics. But how to get this message across and create products that incorporate this?

By co-creating with digital agencies and development agencies, value added data analytics become available as a service to these companies, and in the form of concepts to their end-users

For the distribution of this vision our development platform NICCI is created. This platform incorporates data-gathering, -combination, -enrichment and -analytics combined with innovative UX and (web)tech and provides clear benefits for digital agencies (customer engagement, retention and visualisation) and developers (faster development, components as a service and increasing seamless integration).   

Our products are available via API’s, data streams and complete webconcepts. By co-creating with digital agencies and development agencies, value added data analytics become available as a service to these companies, and in the form of concepts to their end-users. In addition, Newest Industry concepts make use of these concepts as well. With a quick technological pace and an agile approach, we develop and innovate on a daily basis. Just the way we like it!

Conclusion

Big data analytics are hip and happening, but besides that should mainly benefit consumers and other end-users. The objective is to create value adding concepts and services that incorporate analytics and make these high-tech algorithms available and of use to the big public.

Because of this high value added mission, we strive for best-in-market analytics and results. Our partners’ and own concepts are placed in primary processes of consumers and end-users. In order to keep high levels of customer engagement and retention, quality must be over-par and feedback must be taken into account every step of the way.

Evaluating the development process, also for analytics based products and services, iterative and agile are the way to go. By starting from our own values and vision on a market and combining these insights into services and concepts we are able to create viable products and services within a short timespan. Based on feature roadmapping, forward planning and feedback integration, we keep track of where we wanted to go in the first place  and combine our own route with customer experiences and feedback along the way.

Besides having a clear view on business & concept development, processes and technology, our company is characterized by incredibly talented, engaged and friendly staff. Together we create an ideal culture for innovation and customer satisfaction!