Chances are, this is probably the first time you've evaluated an MDM solution, and by now, you know there is A LOT to consider when evaluating vendors. But before you go signing any contracts, be sure you know exactly what you're signing up for.
2. 2
Part 1: Organizational Readiness
• What Does “Ready” Look Like?
Part 2: Defining the Why
• Justification – Prioritization - Rightsizing
Part 3: TCO Calculation
• Solution Complexity Drives TCO
Part 4: Program Scope
• Quick Wins – Where to Focus – Implementation Styles
Part 5: Evaluation Pitfalls
• Business Outcomes – Selection Criteria – What to Look for
Part 6: Beyond the 1st Use-Case
• MDM as a Way of Life – Operational vs. Analytical MDM
PANEL TOPICS
3. 3
Bill O’Kane
Former Gartner Analyst and Profisee VP & MDM Strategist; Bill served for eight years as Vice President of Data and
Analytics and Magic Quadrant lead author at Gartner.
FEATURED SPEAKERS
Christopher Dwight
VP of Customer Success at Profisee; Christopher has been in the enterprise information management and master
data management (MDM) space for more than 20 years.
Harbert Bernard
Value Management Consultant at Profisee; Harbert utilizes his expertise around building business cases for
investments in technology to develop BIRs (Business Impact Roadmaps) for a range of enterprises.
Martin Boyd
VP Product Marketing at Profisee; Martin has over ten years’ experience in MDM, governance and data quality.
4. 4
“
IF YOU DON’T KNOW WHERE YOU’RE
GOING ANY ROAD WILL GET YOU
THERE.
- LEWIS CARROLL, ALICE IN WONDERLAND
Business outcomes, not capabilities
Remember you are evaluating a platform, not an app!
Capability driven evaluations - misleading
"Customer 360" is not a business case!
What are your selection criteria?
How to structure an evaluation process
Your data, not theirs (& use realistic volumes)
Evaluate against BUSINESS use cases – do not focus on features (then ask HOW did you do that?)
Avoid inflexible eval processes (often long list of features) – level playing field is ‘fair’ but unlikely to result in good decision
Properly staff eval – Have available manpower to examine the vendor response – need to allocate time
Product features that sound great and demo well, but are never implemented
ML for matching (test your vendor! Need real world examples)
Automated metadata discovery
Features that rely on high quality data (that you don’t have!) – trust scoring
Differences between IaaS, SaaS, PaaS
Technology fit – match to existing skills
What to look for?
Realistic TCO for out-years
Look beyond first use case
Effort & licensing implications – need DETAILED estimation of services
Configuration vs customization – need detailed quote
Identify core functionality vs. work arounds – “HOW did you do that?” (workarounds, vs core functionality)
Is vendor willing to lift the hood? Why won’t they be transparent?
Ask for line item quote – can be surprising!
Ask for installation guides – how many, how complex?