In dynamic or even turbulent times, insights into what is happening are highly valuable. Understanding the customer and consumer to better serve their needs is crucial for success. Thus companies – small and big – are working on becoming more data-driven. Being able to incorporate insights generated from data into decision making is desirable for many. So, it seems only logical that Big Data and analytics solutions are top priority for many enterprises.
The situation today
The world is constantly changing, and companies need to adapt to change. Sometimes this needs to happen in a short time. Companies need to navigate uncertainty to be able to succeed. Customers have different expectations today compared to just a few years ago, and competitive pressure is at an all-time high. Because of the technological progress of the last two decades, the development of digital and digitally augmented products is at the top of the list for many, and all too often something that has not been done too often yet. Apart from that, digitalization in different areas of the company provides untapped potential for many. Yet many companies are struggling with prioritizing day-to-day work and strategic initiatives.
Benefits of being data-driven
Data-driven companies collect data points and analyze them to better understand what is happening. This leads to a better understanding of the customer, which is a major aspect of being customer centric. Needs, wants, buying habits, buying decision drivers, usage of the products or services offered is all important to understand. These insights In the hands of the right people can drive improvements towards a better customer experience. Insights about business operations can help to achieve efficiency gains. Collecting and analyzing the relevant data leads to a better understanding of operations and to identify potential improvements as well as support priorization of activities. Companies that capture the right data and make them influence their decisions gain confidence in what they do. A facts-based approach to innovation, where ideas are backed up by evidence from the data has the potential to be more targeted. Collecting the right data to test assumptions can further enhance the chances of success.
Being able to understand and inspect what is happening and adapt in short cycles can be a major success factor. This applies to improving the customer experience, the products or services portfolio as well as gaining efficiency and increasing resiliency of operations. Thus, the goal of being data-driven is to better serve the customers and consumers.
For example Rosenbauer International AG, one of the world’s largest manufacturers of fire-fighting vehicles, equips it’s vehicles with 150-200 sensors. The data gets processed in a cloud environment and guides Rosenbauer to provide a better service and drives product development. Through predictive maintenance the customers profit from an increase in reliability of their mission critical assets.
Another example of a company demonstrating the value of data is Frauscher Sensortechnik GmbH. With its sensors and a modern processing solution that consist of an edge solution and a powerful cloud backend, Frauscher provides insights that increase train safety, for example weather a track section is really clear.
Challenges
There are many challenges to overcome to become a truly data-driven company. Data must be available. That means collecting the necessary data as well as making data that is already there accessible and useable. To make this happen, companies must address challenges on different levels: governance & compliance, data security, connections between different systems, metadata, data catalog, quality measures, maybe anonymization and other preparational work. That means that many technical questions need to be addressed.
The longer a company exists and the bigger a company is – especially if mergers & acquisitions took place in the past – the more complex the technical landscape and the more heterogenous the data. Today’s reality is that data is often spread across different infrastructures: on-premises, private and public clouds and SaaS-products. Data can come in all kinds of formats and transfer costs might be prohibitively expensive.
Apart from that, the market is full of technical solutions that promise a lot and shortcomings often become visible late.
However, the job isn’t over after companies solve the technical hurdles. The elements of being data-driven need to be incorporated into the organization. This requires data literacy, and all too often changes in the culture. To be truly data-driven, just having the data isn’t enough – the data needs to be analyzed and interpreted before it can drive decisions. And to make this happen it must be discoverable, and well-explained to allow self-service usage.
Success factors & Recommendations
So, the big question is about how to become a truly data driven company? First of all, companies should be clear on the goals that they want to achieve before starting a big project. If you know what you want to achieve a good starting point is assessing the current data landscape and identifying blind-spots and high impact use cases. To become more customer centric, you should already focus on the customer needs and behavior right in the beginning. Analyze what is required and use these findings to prioritize work. Being data-driven means insights drive better decisions and ideally accelerate making them.
A more technical assessment that focuses on the current capabilities should follow.
We recommend analyzing where data is missing in the organization, and to review the processes and the pathways to get the right data. How much effort is required? How big is the impact? Which data is needed, and what is already available? How complex is the process? How long does it take? Which steps are the ones were the most friction is? Focus on these and never forget your overarching goal: Bring high-quality insights to the people who need it, were they need it and when they need it through on-demand and self-service or, even better, directly integrated into the tools they use every day.
When it comes to technical solutions, a cloud-based approach (link to expert view), should definitely be evaluated. Making use of the flexible and scalable infrastructure of the public cloud has proven beneficial for many especially in the Big Data and analytics space. To avoid capital expenditure and to get started without delay, the public cloud is the way to go for many. Companies who cannot use the public cloud – e.g. for compliance reasons – can still profit from a cloud-based approach by utilizing an existing private cloud solution or setting up a new one.
Still, all the data and analytics capabilities are worthless if decisions are not driven by insights extracted from the data. The organization needs to adopt evidence-based decision making and make it a default. Data-driven culture starts at the top. Leaders must practice the desired habits and lead by example.