CIOs and other business leaders must be able to see the whole picture to make good decisions. In organizations, however, data resides in multiple different systems. More often than not, it’s structured in an inconsistent way across the organization and data quality can vary a good deal. This makes visualizing the big picture virtually impossible.
The first step towards getting actionable data is to integrate it all into one place and harmonize it into a common format. Organizations must create a “canonical” data model, or its “data law.” By doing so, they can define a single way of describing data elements so that the term “billing address”, for instance, means the same thing in the purchasing system as it does in warehouse or billing systems.
Another aspect to take care of is that the data should be easily accessible by all groups in an organization. If not, data silos are formed. Such siloed data creates barriers to data sharing and exchange and collaboration across myriad departments. Owing to inconsistencies in data that may overlap across silos, the quality of data suffers. When that happens, it’s hard for leaders to get a holistic view of company data. And ultimately, decision-making suffers.
The key is to leverage a data integration solution that can enable businesses to consolidate all data streams and make them accessible to all business users - at speed and scale.
But before that, organizations must utilize data preparation methods as their ability to make decisions will be dependent on how well they prepare their data. For better understanding, we have listed three steps toward data integration for good decision-making.
1. Firstly, companies must start by discovering what they want to use the data for. This will inform what data they need and how often they will need it updated - whether in a periodical batch manner or in real-time.
Along with data standardization, companies will probably find that it also needs to be improved in quality. It may be incomplete, imprecise, or missing entirely. The time that’s necessary for collecting and reporting data also needs to be harmonized across the whole organization.
At this stage, organizations need to define the organization’s data governance policy in regards to national, international and industry-specific regulatory compliance. It’s also pertinent to enable data ownership to everyone involved instead of just a few people in IT or compliance.
2. The next stage is to use modern data integration solutions to garner data from different organizations’ systems and then harmonize it, cleanse it, and integrate it to deliver actionable insights and ultimately make decisions.
With rapid advances in Artificial Intelligence and Machine Learning technologies, companies can map complex customer data at speed and then transform and integrate it into a data lake, where it can be analyzed. Even non-technical business users can leverage these solutions to map and integrate large volumes of complex, bi-directional data while enabling IT to focus on other important tasks. Since all departments have access to the incoming data (of course authenticated ones), the problem of siloed data also minimizes.
3. When the technology used is quite similar, any difference must lie in human behavior. Many software solutions are more specialized than others. If the organization has intimate knowledge of the user's industry or business function, it will make a huge difference.
If the software solution provider is well aware of what decisions the user needs to make, it'll also know what data will help the user make these decisions and how the user needs that data presented. Having this knowledge can help the provider build pre-configured models that yield business value straight out of the box. This is an essential differentiator.
Beyond that, creating a data culture is also important. The organization must convince everyone who produces or uses data about the importance of data quality through leadership and communication. Business people must take ownership and carry out data-driven operations. It makes an organization’s, especially IT’s, job less frustrating, and it also makes it easier for them to improve ease of doing business and deliver delightful CXs.
Organizations that use all these steps should reap benefits:
Integrate customer data in minutes to speed up insights delivery and decision-making.
Put IT in the role of governance by empowering business users.
Improve ease of doing business with partners or customers, deliver delightful customer experiences, and ultimately grow revenue.