What Is a Data Driven Business Enterprise?
Tracing All Business Goals to Data
The Data Driven Business Enterprise starts with a business strategy that creates the goals of the business. These goals are accompanied by metrics that measure to what extent the goals are attained. The metrics are influenced by business use cases that if fulfilled will impact them positively. Finally, and most importantly, is the data necessary to execute the use case successfully is defined.
All four of these elements need to be connected with deep traceability constitute what a Data Driven Business Enterprise is. In this article, we will explore why becoming a Data Driven Business Enterprise is crucial in becoming a modern, next generation, and progressive business that differentiates itself tangibly in the marketplace. To become a Data Driven business, a new way of thinking is required.
Data as the Foundation of a Business Strategy Requires a Mindset Shift
A Data Driven Paradigm requires businesses to shift its thinking away from capability driven use case fulfillment to data driven. Business capabilities are a necessary means for fulfilling use cases, however, they are not the end. Rendering functional capabilities is a vehicle only. Powering this vehicle is the data. This is precisely the mistake many businesses make in their Digital Transformation programs where desired capabilities are described that will fulfill its use cases, but the data is left out of this equation. All business capabilities require data, but the mindset shift is positioning the data as the driver of the capability’s value vs. the capability requiring data to function. Further business differentiation comes with infusing new and different data to enable use cases that might not even have been envisioned. This art of the possible is in itself Data Driven. The main point here is it is the data that is the special ingredient that transforms business capabilities enabling them to be cutting edge and inventive.
An example of companies not placing data as the foundation in their business strategy is commonly seen in company’s Digital Transformation program where the goals are based on increasing user experience (UX) by creating an “omni channel user experience”. This capability is commendable, but it alone will not provide differentiating business value thus leading the program to failure, because while providing a cool looking UI is nice, there is no differentiating capabilities. Taking into account what new and different kinds of data can be used to improve UX capabilities provides the value the business seeks.
The Data Driven Paradigm Manifests Itself Many Ways
Being a Data Driven Business Enterprise impacts almost all aspects of an organization most specifically in how business initiatives are delivered. Leveraging the value of being Data Driven requires a retooling of key execution underpins such as the delivery organization, delivery methodology, and business road map. Each of these underpins are anchored by architecture changes that enable the Data Driven Business Enterprise.
Evolving how business programs are delivered takes advantage of the capabilities enabled by being Data Driven in a very differentiating way. For example, in becoming a Data Driven Business Enterprise, you can expect to lower delivery costs and increase speed to market as well as advanced new capabilities.
Historically slow and costly traditional approaches do not supply the business agility necessary for today’s modern businesses. Let’s examine the differences in more detail.
The Architecture in a Data Driven Business Enterprise
Anchoring a Data Driven Business Enterprise is a next generation architecture and supporting technologies that are designed enable the infusing of new and different types of data with the business agility necessary for modern businesses to not just succeed, but to differentiate themselves as cutting edge capabilities are implemented. A key element of the architecture that facilitates this value is a data hub which enables the quick loading of data without substantial data modeling up front. The data hub also supports the commonality of data between the operation and analytics environments which is crucial in minimizing duplicate data. A data hub additionally is able to process easily data that is of substandard quality. Also, and just as importantly, it has the ability to quickly curate and publish data to back end systems or online applications as well as receive and publish analytical data.
In traditional architectures, substantial data modeling is required to be done up front and there is normally no ability to process low quality data in the database. Data is also in silos and therefore not a trusted single version of the truth. Additionally, data especially analytical data, is not easily published for operational purposes. Lastly, data is transformed in large chucks that are costly and slow to deliver.
The Delivery Organization in a Data Driven Business Enterprise
Taking full advantage of the power of a next generation architecture, the company’s human capital is organized and compartmentalized along the functional components of the data value chain. Examples of some of these components are data provisioning, data curation, data enrichment, and data publishing. Teams are allocated across these components enabling continuous and incremental delivery that is swift and with agility both of which are necessary for a modern business enterprise.
In traditional organizations, teams are allocated by application or business function which fragments and duplicates resources increasing cost and slowing delivery speed.
The Delivery Methodology in a Data Driven Business Enterprise
A standard for a modern business enterprises is to always be agile in its delivery methodology and driven by manageable sprints tied to the use cases which are a priority for the business at the time. This is a crucial factor in increasing speed to market of business capabilities. To attain this goal, a next generation architecture is required that is designed to deliver data in micro chunks as small as just one data element if that is what is prioritized in the backlog.
In contrast, legacy type architectures and technologies especially analytical applications, that attempt to employ agile methodologies very often do not save any time or cost, in fact, commonly increase both is seen. This problem is rooted in that fact that it is very hard with legacy technologies to deliver small chunks of data easily and when delivered require a huge amount of regression testing for each sprint making the overall delivery slow and costly.
The Business Road Map in a Data Driven Business Enterprise
Becoming a Data Driven Business Enterprise requires a substantial mind set shift in how businesses approach and plan delivery programs. The underpin of this shift is based on the ability to deliver smaller chunks of data incrementally something not possible in the past. This ability has a dramatic and transformative impact on roadmaps in that they can now be driven by use case fulfillment instead of some large data milestone. This is a game changer for businesses as it enables the business agility necessary for for early wins something that is more and more required in today’s modern business enterprises. Smaller data chunks also allow for consistent and measurable progress for large data programs in lieu of the “big bang” implementations of the past that usually do not meet business expectations, because the business does not know ahead of time with precision what constitutes fulfilling the requirements. Iterative delivery, with a feedback loop, is clearly a standard for the future for progressive businesses over pre conceived requirements.
Also, in a Data Driven Business Enterprise, runway activities are more focused helping the business understand where the gravity of work is likely to be, because the analysis can be decomposed based on smaller data chunks. This enables the subsequent program delivery work to be proactively shifted to the places it is most needed.
For example, a large data program’s road map driven by use case fulfillment will focus on the analysis and rationalization of output data requirements and specifications. These are then broken into increments designed to deliver precisely and only what is required to fulfill the business use cases that are a priority at that time. This provides for a huge uplift in business agility not seen in the past. In contrast, traditional large data program’s road maps focus on large data milestones which can’t deliver incremental value nor early wins.
For businesses to differentiate themselves in the modern world, strategic goals need to be met quickly and with consistency, but also driven by art of the possible capabilities never dreamed of a few years ago. Becoming a Data Driven Business Enterprise enables these goals. Don’t make the same mistakes that many companies make in Digital Transformation programs that emphasize the wrong things. Successful businesses link their goals with deep traceability to data to provide tangible business differentiation that separates them from their competitors. Most importantly, successful businesses are pushing the envelope around using new and different types of data to quickly implement game changing capabilities that enable them to win in a competitive marketplace.
The Data Driven Business Enterprise is the basis of a modern, forward thinking, and next generation business that wins!