written by Joy Gupta, COO at Sparkline
With the sharp focus in recent times on data and its related benefits if used effectively, governance of data often takes centre stage in many discussions.
There are many aspects to Data Governance but simply put it refers to the overall management and execution of data employed in an organisation, whether that relates to security, availability, usability or integrity.
In particular, in the field of Digital Analytics, some of the common pitfalls in not deploying such rules could cause issues such as the data not being actionable, difficult to integrate across silos and insights being too slow or inaccurate.
In a study conducted by Mckinsey, opinions show that breakaway companies are 2X — 2.5X more likely to have a data strategy and strong data governance structures.
Deploying an effective data governance strategy can incorporate the following areas :
- People — Hierarchy and Structures
- Systems & Processes
- Tools & Sustainability of them
This often takes long setup times, requires top-down buy-in and needs to be followed up with effective communication across the organization.
In Sparkline’s experience and specifically within the ambit of digital analytics, we find regularly auditing web analytics tools as central to driving this strategy and with that in mind have developed Sparkline Auditor to address this.
As is well known by digital analytics practitioners, implementation of web analytics tools often break due to reasons such as :
- Change in site functionality
- Inefficient and incorrect usage of the tool
- Tagging duplication and related issues
When this happens, erosion in confidence around the analytics software and poor decision making follows.
Sparkline Auditor audits your web analytics implementation and flags issues that are causing this erosion in confidence including checking for questions such as :
- Are your ecommerce numbers accurate?
- Are your campaigns being tagged correctly?
- Are your traffic numbers highly inflated due to spam?
- Are you tracking Personally Identifiable Information (PII) in your web analytics software ?
These checks especially when done after changes in site functionality, migration and website launches become very useful but we find businesses benefiting most from running the audit quarterly as part of their data integrity planning cadence.
This is a specific example but an important step in getting your overall data governance strategy aligned to your goals.
In conclusion, you can use the following steps as a good starting point in your journey to build data governance maturity and evaluate how you are performing against these metrics :
- Align your data governance plan to overall strategy
- Build systems & implement processes that enable a single, secure source of truth for your data
- Assign resources that champion your governance strategy at every level ensuring compliance
- Audit and implement tools that focus on ongoing governance
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Joy is a business transformation enthusiast who enjoys conversations around growth, operational and digital initiatives adopted by enterprises