When It Comes to Big Data and Cloud, Continuous Innovation is the Model
During the 2008 election campaign, Barack Obama denounced his opponents for advocating "change" as an electoral argument while belonging to the government party that "had changed nothing." He approached the situation with humor, employing an expression well-known across the Atlantic: "You can put lipstick on a pig, but it's still a pig."
This expression could also be applied to some software companies. With the success of the Cloud and Software as a Service models on the one hand and the increase of subscription services on the other, it seems that software offered in the form of a subscription is becoming the new standard. In fact, as early as 2015, Gartner estimated that by 2020, 80% of vendors would adopt a subscription model.
This change in the way companies use software has frequently been said to reflect users' demand for flexibility. Indeed, companies are no longer willing to lay out a major investment to get equipped. They are looking to prioritize variability in their spending based on usage and to ensure they benefit from the value of the software before making a long-term commitment.
But while business models are moving toward subscription services, if technical developments don't keep pace, a piece of the puzzle will be missing: And it’s a crucial piece.
Subscription Services: Beyond Cost, Bringing Innovation as Close to the Market as Possible
Let's forget for a moment the how the software is billed and take a look at another essential aspect, the value that it offers the user. This is where the real challenge is: The ability to provide users with frequent releases (to be as close as possible to current technological innovation and customer demands) becomes a means for differentiating between two commercial subscription offers.
A perpetual license mode also allows for software updates. However, the rhythm of updates and the frequency at which they are available to users cannot be compared with the ongoing agility and innovation offered by providers of subscription services. This is not related to how their software is marketed, but to the vendor's intrinsic organization and ability to establish a continuous cycle of innovation and to transfer this innovation to his customers.
Big Data and Cloud: Continuous Innovation is the Model
The world of Big Data and Cloud is an obvious illustration of the need for continuous innovation. The speed at which these technologies become obsolete requires users to adapt at an unprecedented rate. The platforms adopted by customers today can become obsolete in just a few months (Spark replaced MapReduce in record time; Spark 2.0 is a revolution compared to Spark 1.6). It is essential for integration, processing, and operating software vendors responsible for these massive volumes of data to get as close to the market as possible, which means complying with key standards such as Hadoop, Spark, and BEAM and align themselves with the open source communities defining them. In practical terms, a company needs to anticipate the product roadmap generated from these innovative technologies to adapt that of its own products. This makes upstream preparation possible for integrating new capabilities, which will benefit end users as soon as the platforms put them into production.
While open source—based on technological openness, community and collaboration between various partners—is particularly well suited to this model, it's not a secret that the new generation of vendors has developed a specific organization designed to offer continuous updates. And subscription services are a way to finance a policy of continuous innovation. In the former model, with a so-called "proprietary" software solution and a perpetual license format, it took 18 to 24 months to benefit from new features. At the rhythm of machine learning advances, IoT, and real-time and streaming data analysis capabilities, the model that consists of delivering new versions every 18 months is simply not viable for the user.
Supporting the Emergence of New Data Uses
Modern solutions for big data and cloud integration must be at the front lines of technology innovation, not only to address customers various and rapidly evolving challenges, including innovation, sustainability, agility, and economies of scale, but in particular, to encourage the emergence of new data uses—streaming, real-time and self-service—themselves a vehicle for competitive advantage.
The speed at which these platforms become obsolete is palatable. In the past, a technological feature could last for years without risk of becoming obsolete (e.g. SQL). Today, technologies become outdated far more quickly. Competition is fierce between companies using digital transformation as a strategic lever for performance and competitiveness. The result: users of these technologies need the ability to easily adapt from one standard to another. That’s why it’s so vital to select a vendor that is in line with the times so that you may continuously benefit from market innovation, and of course, easily recognize when it’s just a pig in makeup.