Organisations struggle to become data-driven if they retain traditional siloed business functions. The hand-offs resulting from their differing business goals and inter-communication overheads incur too much inertia.
The real question is: How do you become outcome driven? It requires those who interact with customers to understand what is happening in context – being informed – to be empowered to make decisions and to be equipped to act according to the business goal.
It takes an end-to-end approach to become an outcome-driven organisation
I have shown how to build a slice of a data pipeline in previous posts on my blog. This end-to-end approach is the enabler of shared situational awareness. Data is available from source in a shared platform, which in turn feeds information to all parts of the business. However, vertical organisation silos also need to be dissolved in favour of outcome-driven value streams. Those at the front line must be able to see all the way back to the start of the information cycle safely within the organisation’s information governance policies. Everyone then has improved and timelier shared awareness.
Each area of the business that interacts with customers operates as a business value stream. These streams enshrine the concept of bringing the work to the people, rather than shipping people to the work. This increases quality and employee engagement and reduces internal conflict.
Consuming higher value services releases business capacity
Teams are assembled for value streams. They are multi-disciplinary and obviate the need for traditional IT programmes and shared services. The maintenance burden of sustaining existing IT systems is reduced because migrating workloads to the cloud means that previously highly sought after, shared technical expertise can be dedicated to each business area. Each business area can concentrate on optimising its outcomes.
Teams are able to find and access the information they need using the data platform and configure a pipeline to produce the insights they need for decision making. This employs techniques including data analysis, identifying patterns, algorithm development, and more. The pipeline can be augmented by AI and machine learning for greater automation and accuracy.
Micro-services architectures provide teams with the technical capabilities to act, but that is the subject of a future post. Suffice to say that this offers a step change in automation and agility.
Such automation enables business operations to react more quickly to changes. It frees up time for people to learn new skills, for better quality engagement with each customer and to focus on tasks that rely on imagination, intuition and empathy.
The profile of technical skills an organisation needs to compete has shifted
Each business area will use the platform to easily create, maintain, grow, shrink and decommission its own systems. They will be able to exploit automation, sophisticated analytics and machine learning. As I have shown in previous posts, the barriers to deployment are so low they will be able to start small, experiment and enhance capabilities in days or weeks on the platform without creating unsupportable or under the desk IT.
Only then can you truly become data driven and maximise the benefits of a data pipeline.