As software continues to take over the world, traditional players such as communication service providers, banks, public authorities, hospitals or car makers need to digitize their businesses. Customer journey, consumer need anticipation and data leveraging, and optimizing business KPIs (revenues, churn, costs…) have become common terms.
How? By using the ‘secret sauce’ used by Amazon, Apple and Uber over the past ten years. This is to say, assess algorithms, look into respect for privacy, ensure technology optimizes financial objectives AND customer satisfaction instead of promoting financial objectives over individual rights.
Whatever the sector, whatever the service, many cases require the ability to collect and leverage activity and mobility data and rely on multiple capabilities to compute appetite scores. AI is instrumental in making sense of and creating value for customers. An example of this is analyzing large data streams in real time, behavioral insights, trends, patterns enabling to detect fraud, or apply machine learning algorithms to predict business KPIs.
These very generic capabilities become essential as they are instrumental in rolling out a strategy aimed at applying digital formulas to serving business objectives in the 21st century.
Any well-orchestrated move towards digital transformation requires a flexible platform with the above-mentioned capabilities. These capabilities come in the form of modules. But what is more relevant? Open-source modules widely available on the market? Proprietary software with specific purpose?
Open source can be a good choice for exploration, such as, when trying to identify new data monetization strategies that have not previously been assessed. Or when trying to bridge a gap in functionality between two pieces of software in order for everything to work together. However, to roll out at commercial scale a digital strategy relying on cases with proven track records and advantages, opt for commercial software.
The reason for this is two-fold:
From a technology standpoint, assembling many pieces coming from multiple sources is cumbersome, inefficient, difficult, and in most cases, time-consuming and risky. In that regard, a well-designed piece of software coming from a single commercial vendor is always superior.
From a business standpoint, business-specific adjustments made to a commercial product always stem from the past experiences of the vendor. Customers benefit from improvements recommended by existing customers and from a roadmap. This ensures permanent progress as well as faster returns.
IT organizations care about maintaining control over their work product. This is why they should choose commercial software with enough scalability, through well-documented APIs and ideally a framework to either personalize or extend the commercial product. This strategy presents the least risk, especially in terms of time to market while staying relatively independent from the vendor, and making sure the internal development workforce will add value by customizing the platform and integrating it with third-party products already present in the IT ecosystem.
As a matter of fact, one comprehensive platform with all the above-mentioned capabilities can support several cases, digital services and data monetization strategies in various industries. By adopting such a platform, governments and companies will start to capitalize on their data troves. And in that domain, the more, the merrier! As data is gathered from multiple sources - ideally different departments of an organization - the combination of such data will help create correlations that did not exist before and identify patterns that had previously gone undetected.
Breaking silos is a unique opportunity to modernize an organization by reassembling what should never have been separated in the first place. This is one of the major steps to be taken by historical players in different industries who now compete with the recent unicorns of their sector. These recent players are organized all around data. Data is shared and made available across the entire organization. To remain relevant, traditional business and governmental bodies shall first and foremost break silos and engineer data platforms in order to fight with equal means against the new champions of the digital era.
Moreover, effectiveness is higher when getting data streams to flow towards a unique monetization engine. It is more time efficient to collect, clean, organize, and make sense of data in a single place, as opposed to implementing new infrastructure for each new use case. This is why using a comprehensive platform that leverages data and enables a broad variety of cases is the only effective and cost-efficient way to roll out a digital transformation strategy in the mid to long term.
Intersec’s findings over the past years indicate that this strategy can generate massive returns for end users. Communication service providers among our customers often achieve tens of millions, sometimes upwards of a hundred of millions of Euros/Dollars in incremental revenue. Contextual marketing strategies often allow higher take-up rates in new offers by identifying and seizing opportunities to anticipate customers’ needs. Governments engage in a similar strategy to achieve increased population safety. They monitor anonymous citizens’ locations in order to manage crises in real-time with location-based communication, as well as a direct view of population density and how it evolves as they take steps to handle a situation. Many sectors will find ways to increase the relevance of their messaging towards their customers, and better understand what people need and when they need it. Meanwhile governmental bodies and cities will implement strategies to modernize our lives by making sure data serves us and protects our identity, while adhering to the highest ethical standards.