In this new era of digitalisation and at lightning speed, businesses at all levels, from the smallest to the largest departments, are mobilised to draw the path of a successful data journey. They regard data as the untapped yet most essential asset to embrace, but the road ahead is scattered with traps, pitfalls and challenges.
- Data-drivenbusiness and data silos:
Data-driveness is about building leading technology solutions, amplifying capabilities and most importantly, creating a culture that acts on data. Often measured in terms of level of analytics, data maturity or applications, what makes up a data-driven business is most likely its agility in using data to power decision-making and value-creating applications.
In this race for data-drivenness, a lot of businesses activate their hyper-speed mode to adapt to the unprecedented wind of change that has been blowing over a radically new business landscape now more than ever capitalising on a new form of precious resource: data.
In their expedition to the data destination, each business unit tries to map out the best route and tools, build processes, identify best practices and define what might look like the winning strategy to reach the data road. Filled with good intentions, these businesses strive to elevate performance by overdoing. This might result in success stories and small wins, but there are a lot of pitfalls and challenges that lie ahead. The most common and biggest pitfall is to attempt to create an overdose of efficiency by implementing best practices and building ultra-secure fortresses around their data which ends up doing more harm than good. Other common pitfalls of data-driven projects are the lack of communication, process duplication and data isolation.
All of this leads to data silos. Also known as information silo, a data silo is a repository of data that is not part of an organization’s enterprise-wide data management. These silos reveal a situation where one or more information systems or subsystems that are conceptually connected, are incapable of operating with one another.
Similar to working bees in a hive, each business unit tries to come up with the best methodology for gathering, managing and effectively analysing its own data whilst ensuring that it is well-guarded and invisible to onlookers. By doing so, they manage to create intra-department value and efficiency yet make it impossible for that efficiency to neither spread across the frontiers of that specific department nor beyond.
- Example : The 360° customers view, an orchestration of data-driven marketing.
Ultimately, businesses want to offer the best possible customer experience and allow for a unified view of all customers' touchpoints.
This unified view is created by aggregating hard and soft data captured through the different interactions, channels and data sources enabling users to view and analyse all the data collected for each and every customer in one place.
A 360° view helps you make the right offer to the right person at the right time. What it really means from a business perspective is enhanced customer intelligence, hyper-personalized experiences and higher brand loyalty.
The implementation of such a view seems easy but nevertheless, it is much more complex than one may think, in a space that does not allow the free flow of data building a 360° consumer view becomes somewhat challenging if not impossible.
Even though there might be countless possible reasons for the failure of building a consolidated view of your customers or any other data-driven initiative, for that matter, data silos are most likely the most plausible reason for them all.
Customer data comes in a variety of forms from a wide array of sources and bringing it all together can be challenging. Data exist as user profiles, purchase records, form entries, or click-throughs. The systems where all this data is stored often don’t communicate with one another and lead to data silos.
When building a 360° view, we might need to cross internal data from one or many ERPs, back-ends, CRMs and some real-time customer behaviour data from the website. Ideally, all systems provide complementary data about customers, their user profile, history of purchases and online behaviour and when all linked, can create consolidated intelligence. However, if the systems cannot communicate with each other, then, the data sets cannot be linked, hence are invisible to each other.
Surviving as a mainstream business today means being data-driven. Yet, becoming a data-driven organization does not happen overnight, it takes a lot more than a few resolutions and a well-articulated data strategy. You cannot stop these data silos from emerging, they describe isolated islands in an insular system that are discovered when discrepancies occur. The only thing you could do is prepare your data projects as much as possible and think of ways to manage them.
Businesses that fail in managing data as an asset, building a data culture and using data to drive innovation will inevitably fail in becoming data-driven.
Digazu can help empower and accelerate your journey towards data maturity by giving you the means to efficiently manage and leverage the value of your data. We also help you avoid and manage data silos.
Learn how you can become data-driven in just a couple of clicks with us!