Breaking the Data Paradox

By Sandip Chaturvedi | @intelia | May 17

– Data is critical but doesn’t require as much time and effort!

– Data is critical but ROI is more critical!

– Data is critical but it is expensive!

– Data is critical but I don’t need it!

It is not uncommon to have not come across these statements once in a while. Is it un-natural for these paradoxes to exist or do the enterprise data strategies augment these feelings?

 

In a lot of situations, we find the Data & Analytics Strategy (hereafter referred to as DAS) is either:
  • not present at all and/or driven by a single business outcome rather than the enterprise OR
  • does not align with wider Business Strategy OR
  • has poorly defined DAS target state and does not articulate the roadmap to success OR
  • the most common observation – Data and Analytics come last OR
  • does not apply the lean method
Some of the commonly observed symptoms when you are lacking an efficient and fit for purpose DAS:
  • Lack of business engagement and senior leadership direction often leads to half-baked DAS that does not meet anyone’s needs
  • A Data driven organisation struggling to deliver business value – This can be most probably due to missing/vague data goals and enterprise target state or perhaps the data ecosystem is too complex or both
  • Lack of Data Literacy within the organisation – It is very important to understand that Data Literacy is as critical as data itself, for any organisation to adopt. While a group or team understands the data and is skilled in using it, the significance of the same is either not widely understood or lacks commitment from every member in that data chain. Data Literacy is a critical work that an organisation must undertake
  • The enterprise reference architecture and building blocks are often missing and even when present, it is not widely published for teams to align their solutions to it
  • Unable to define high-value (immediate business value) data vs low-value data (for later use) and lack of data ownership
  • Poorly implemented DevOps or MLOps leads to longer times for Continuous Integration (CI) or Continuous Deployment (CD)
  • Organisations struggling to contain data ecosystem costs leading to poor ROI, missing SLA’s and consequent lack of business investment
  • A Business change takes too much time – Either the Data Ops is absent or even when set up there is a lack of investment in the right resources or time
  • Encouraging siloed approach across business functions to solve for business problems due to missing data, lack of appropriate tools/approach
  • Unavailability of a platform (or missing capabilities and/or tools) for data users to collaborate and exchange ideas for solutions or discuss common business problems within the organisation
  • Buying/Selling a new business – Mergers and demergers
  • Misaligned or missing mid-term or long-term data roadmap or does not have any or both
  • A logical Enterprise Data & Analytics Platform is missing or unclear – missing Enterprise reference Architecture or missing solution building blocks etc.

So, if you have any of the above symptoms, we highly recommend you review your Data & Analytics Strategy. Your Data ecosystem is as strong as your weakest strategy link.

Sharing a few of our experiences where we have been successful in breaking the paradox:
– Scenario 1: Corporate Strategy and DAS is not aligned – we aligned the DAS with Corporate strategy and made sure that DAS is fluid enough to change as Corporate Strategy changes
– Scenario 2: Overly complex Data Strategy – we followed the Lean method to build the DAS. This is one of the approaches we advocate to our customers for developing the DAS driven by the business drivers and data capabilities.
– Scenario 3: Wrong tool selection / underutilised tools – we reviewed the usage of tools/services in the data ecosystem and provided recommendations based on the capability the organisation needed for consolidation and retirement.
– Scenario 4: Decentralised/No cost management – we helped build a single pane of glass for the DAS cost management for the enterprise.
– Scenario 5: Missing or non-aligned Enterprise Data Ops Org – we reviewed the current structure and provided recommendations to reorganise the data services/processes and required alignment of roles and responsibilities.

When you are on the “That’s the strategic direction” path – In the beginning the data will feel expensive because you will buy or build foundation tools, hire skilled people, upskill people, establish the enterprise data teams etc. but, as you progress in building your platform you must be able to reuse, monitor, recover and manage the cost with the right strategy.

Lean Data & Analytics strategy provides long-term direction while at the same time being flexible so that the direction can be tweaked to meet the business outcomes. And this includes the different data disciplines. The mid-term (to immediate) strategy focuses on meeting immediate business outcomes and alignment with the long-term. We specialise in both approaches top-down as well as bottom-up.

In the end: Data is CRITICAL and therefore it requires senior management’s time, commitment, adequate investments, and timely decisions.

Keen to supercharge your data strategy or want some support to build one? – please reach out to intelia for a chat.