What does a company need to consider as it manages its transformation into a digital business? Focusing on business outcomes, the right blend of skills, and robust data governance are key elements. This is the first in a series of posts on the role data governance plays in creating trusted KPIs and metrics that can be effectively visualized and disseminated.
First, what does digital transformation mean? Here are a couple of personal experiences that illustrate digital's impact:
- I recently received a LinkedIn invite from my neighbor. Although we talk, we've never shared any form of electronic communication, so how did LinkedIn connect us? We realized that as we both use LinkedIn on our phones, LinkedIn recommended me as a contact based on our geolocation data.
- I used Uber to find a taxi the other day. Throughout the whole process, from booking to payment, I didn't speak to a human being – the ability to completely self-serve is something that would not have been possible just a few years ago
Technology, data, and the ability to quickly turn that data into useful information are driving new ways of doing business. To keep up and get ahead, businesses need to be able to completely reimagine their underlying processes.
Before identifying how you can leverage technology and information, you must start with the end in mind by understanding your business outcomes, such as creating trusted KPIs to manage your business, and your existing processes. You can then look at ways to reinvent how you work to create new insights with technology and advanced data analytics.
Information governance: Unlocking digital transformation
Achieving these goals requires a unique range of process engineering and advanced analytics skills, underpinned by well-governed, trustworthy data. We have found that many organizations find it difficult to implement an effective data-governance (DG) program due to resource constraints, complex applications landscapes, and inherited, heterogeneous, and outdated IT infrastructures.
DG programs typically focus on the business issues that will give maximum return on investment by centralizing control over information. They require prioritized needs, and a close partnership between IT and the business. The aim is to consolidate and update operational master data at source by resolving data issues in the interim.
As the DG program progresses, however, other stakeholders approach the data governance program owners with new requirements. With more problems to address, the priorities change, and the number of requirements, stakeholders, complexities and source systems explode. In addition, as many business processes are linked to operational master data, changes are complex and time consuming, and can delay business plans. It is hardly surprising that DG programs often lose momentum and fall behind schedule.
We recommend adopting a hybrid approach to overcome these challenges. By including an information-governance (IG) activity in each project, you can create and document information supply chains that populate a new trusted data store, which can then be used by reimagined business processes.
IG focuses only on specific processes and the data they require, which clearly defines the scope. By following the data trail from source to target the data lineage can be tracked and inconsistencies identified. These inconsistencies are resolved, not by changing operational data (which impacts many business processes), but by changing the newly created information data store. At this point, resolution to these inconsistencies can be passed on to traditional DG programs to resolve those in the operational source data.
The information governance approach helps accelerate digital transformation by enabling organizations to decouple the delivery of trusted information, technology, and reimagined processes from the existing landscape and its inherent challenges. In addition, integrating IG within a Lean DigitalSM methodology allows companies to connect technology decisions with business outcomes, and, by harnessing design thinking and Lean principles, achieve the expected return.
In our next blog we will focus on the creation of trusted KPIs using the "information supply chain" approach to demonstrate how you can create data sources that overcome a chief concern in the minds of many: can I trust the information I'm using to make decisions?