Putting some trust in your decisions
When we talk to new clients about Data Governance and Quality, the initial conversations we hear are about it being a “burden”, an “overhead” to implement and manage. A capability that serves as nothing more than creating red tape in agile environments that consume and generate data.
It is not uncommon, especially when organisations believe they have no problem and are happy to continue the way they have for the last 20+ years.
To some extent, I understand it. Having worked in many industries, at one point we were probably all part of it.
The glaringly obvious truth though is that in today's market, if you want to be better than the competition, if you want to transform your organisation, if you want to grow the business, data sits at the heart of all of it. Without a solid trust and understanding of the data, none of this is possible.
The questions we ask our clients are not about technology, not about “do you need data governance”, they are about:
“What keeps you up at night?”
“What are the key things you need to know about your business?”
“Why?”
“What do they drive?”
“If you could make better business decisions what would that mean for you?”
And so on.
They are about fundamental business improvement opportunities.
Data Governance and Quality, much like technologies are enablers for your organisation, they just tend to be far cheaper and easier to implement, and go a long way to underpinning your transformation, growth, compliance and market presence.
If you want to improve your trust in your data and information, reach out to us for a chat, even if it’s to ask some initial advice.
Empowering Digital Transformation through Data Strategy & AI Innovation | Data & Privacy Leader | Speaker & Author
5 年Robin M., Nice take on Trust! I have embraced Data Quality Management, in Enterprises which had sufficiently good quality data. But, they had a challenge of "TRUST". I had to commission data quality assessment, one-time, just to build awareness around "Trustful Data" that comes from elsewhere. This in-fact reduced everyone from carrying out their own quality assessments. On a broader note - Managing Quality of data still builds Trust irrespective of the quality of data. 1. Where data is bad, Quality monitoring, recovery & remediation is required 2. Where data is good, Quality assessment still does the trick! However, Monitoring follows assessment! #dataquality?#datagovernance?#dataqualityassessment?#dataqualitymonitoring
Semi-Retired
5 年Bang on Robin. That one word 'TRUST' needs to be broadcast. It's not about MDM, quality, tools etc. It is "do you trust your data?" This is what I explain to companies. We will improve trust in your data by doing xyz, which happens to be the frameworks and capabilities. Never mention Data Governance, Data Quality, analytics, ML, AI etc. You are touching on a pet subject. The language we use to shift the data dial toward those business outcomes.
Finance Data Reporting & BI Technology acquisition and implementation
5 年Very true Robin, many businesses prefer or without realising dive in the middle ....straight into projects for new systems or digital transformation via a technology led approach They are then left wondering why the outcome is poor to average at best Rather than a burden upfront investments in these areas you discuss, are akin to insurance policies at reasonable cost , to achieve better outcomes on the tech, be it new systems or digital transformations !