Enabling Your Data Driven Organization

Achieving data value is arguably the greatest challenge and opportunity organizations face today.

Accelerated by the pandemic and rate of change, our expectations have evolved and indeed expanded as we embrace an increasingly hybrid world that demands the data capability to be always on, always sensing, and always accessible; real-time. With remote working levels increased by x5, and research reflecting people wanting that flexibility to stay; cloud spending by enterprises rising significantly [59% from 2018 to $73.8M in 2020 IDG]; ecosystem collaboration expanding; rapid advances in bio and life-sciences creating a sphere of influence across multiple sectors; and global data consumption accelerating by 5 Years, these are trends and impacts set to last! I believe we have entered a new era of convergence, partnership and active agile intelligence.

In combination, this has created the four V's of data that are Volume, Veracity, Velocity and Variety which are only set to increase with the advance of ever deeper levels of inter-connectivity through cloud and smart technology integration, OT and IT convergence, and the mainstream rollout and application of 5G. So how do we achieve that vital fifth V of data Value, and what are challenges impeding its actualization?

This is a critical conversation and one I was delighted to unpack in depth with Thomas Harrer, CTO IBM Server and Storage with our full discussion available here. Thomas’s role absolutely necessitates understanding the requirements, opportunities and challenges of clients, and translating these into tangible solutions, supported by the power of partnership, notably the long standing trusted IBM relationship with SAP, so he is perfectly placed to explore these very issues. Here is Part 1 of our key takeaways focussing on the challenges to data optimisation, with Part 2 bringing the catalysts of data value enablement centre stage.

Data Barriers and the Data Paradox

It is becoming ever more efficient to use more data and today we see examples of this from health wearables to autonomous robots and self-driving cars, to everyday organizational life across the world. And this all coupled with the rising investment into the transformation of more traditional business processes to digital, accelerated by the pandemic. The challenge then, is ensuring the understanding, management and leveraging of all this data to attain full value. But this can be complex, involving the bringing together of structured and unstructured data; newer forms of sensor data; the contractual, financial and transactional data that describes the ‘state of the organization’; together with mission critical core systems as well. It is time to get specific, in the same way that we can now tailor highly personalized medicine interventions, we can also design very specific solutions based on data to problems. And to do so we must address the underlying issues of data waste and lack of optimization.

For many organizations today, data volume does not equate to data value, revealing the Data Paradox. Recent research conducted by Forrester emphasizes this finding - although many businesses believe they are data driven, in actuality they are not prioritizing the right use of data, right across the organization. Secondly, although many organizations state they need more data, they actually have more than they can handle. And thirdly, although many businesses believe in ‘as a service’ benefits, only a few have fully made the tradition to this model.

And beyond this, we also see issues of continued data waste, as an example up to 90% of ML models do not make it into full production and data silos persist - a problem for 90% of organizations today. Finally this data juxtaposition is often compounded by issues of Limited Data Access, Lack of Real-Time data, Lengthy Time to Value and High Entry Costs. So we have reached a critical moment of transition in managing this effectively.

‘The core of the data paradox is the discrepancy between volume and value. There is not an equal identity of volume equals value, probably I see it more as a spectrum, there is some data which has perceived a very high value, because it's the critical data of a company. And at the edges, there are more amounts of data that need additional intelligence to get to the value which is in it. And this will happen only if organizations are investing in unleashing this value’. Thomas Harrer, CTO IBM Server and Storage  

So how do we address these barriers and enable data value optimisation at scale? In Part 2 of this series, Thomas and I discuss the role of emergent technology integration, self-service data access, modeling and baked-in governance notably the capabilities of SAP’s Data Warehouse Cloud (DWC) and the power of trusted partnership, plus we review the latest in developing technology trends, from Confidential computing to Open Source. Stay tuned!