Generally sensible throughout but - unusually for Philip Howard's research output -it leaves some unanswered questions.
Even as a statistical forecasting effort, it does leave something to be desired. Rather a lot of tables have been included that don't contribute anythingto the sum of human knowledge - in particular a single CAGR (compound annual growth rate) of 10% appears to have been applied willy-nilly to every single region and sector (confirmed by retrofitting the figures -allowing for rounding to the nearest million). What a shame the research doesn't build on either Bloor or external figures for:-
- likely frequency of application replacement (by industry: Banking hasa more rapid cycle than Trading Companies, and perhaps by context/application type)
- industry/regional growth forecasts (eg from OECD)
- No mention of government / public sector projects This is the biggest area for cockups, especially given the fragmented natureof PFI/PPI in the UK, and similar huckster schemes abroad.
However, the headline figures are worth absorbing, to give an order of magnitude for the market, and more importantly an idea of the extent of project failure.
- 84% of data migration projects "fail" (not delivered on time and on budget)
- Cost overruns average 30%; time overruns average 40%
- Data migration is a $5 billion market this year (or maybe twice that if you throw in smaller projects that come in under the radar for this survery) growing to $12 billion by 2012 (sounds like a lot - but London is spending more than that on the 2012 Olympics...)
At a more detailed level, I'm not entirely comfortable with the attempt at separating "data migration" as a market in its own right from related markets (ETL, EAI, etc). I would prefer to see DM as a particular use case for ETL, EAI and DQ tools; many of the same tools will also have applications for data integration, application integration, business intelligence and other use cases - although mileage may vary.
Howard states that DM only aplies to "one off" migrations and is distinct from data integration; well, yes and no. DM may have to take place over months or years; during that period, "source" and "target" systems will have to coexist somehow. That may be achieved through "temporary" data integration/replication, or by partitioning the data and gradually handing over slices from source to target. Given the ever-changing nature of business, it is by no means inconceivable that the process never reaches its originally planned conclusion (the final decommissioning of the source system). Parts of the "source" may turn out to be worth retaining (ie the economic case for replacement is not viable).
Perhaps the biggest concern I have is that there is no mention of DM as a subset of business change. DM scoping is often imposed by (sometimes poorly considered) "business" considerations and decisions. There needs to be a feedback loop from DM processes into the overall project feasibility, scoping, planning, and costing. How many DM budgets are over budget simply because the budget was unrealistic to start with - because project costing was done using some rule of thumb [eg see John Morris's data migration blog] that happened to be inadequate in the circumstances?
Finally, I am amused (and not at all surprised) to find that hand coding is the market leader at 30%, beating ETL into second place with 28%. Given that ETL tools are often given away with applications, databases, and maybe even with leading brands of Cornflakes it is amazing that this situation hasn't much changed in the last 15-20 years since ETL tools first appeared. I always thought that DIY (roll-your-own for some american speakers) was our (Constellar's) biggest competitor back then - and here's yet more anecdotal evidence. Informatica and other tool developers - not to mention application/product architects - need to understand why that should be:
- no tool is a magic bullet: even a market leading ETL tool may make some cases easier, but can make a few (important) cases much harder to manage (if all you have is a hammer, everything looks like a nail)
- tools are expensive to own: they can be expensive to buy, but much more importantly skilled tool users are expensive to train or hire. The migration skill-base is fragmented (what works for PowerCenter is wrong for Oracle Data Integrator; Ascential does things differently from Ab Initio).
- data migration projects are seen as "boring": so may not always attract the youngest, thrustingest, enterpriseyest architects. Like support, a critical area is treated like a leper in some organisations. No wonder the outcomes are sometimes suboptimal. Those cast into the outer darkness of a migration project eventually either transfer internally (and let their skills degrade), or hop off into a consultancy or frelance contract to rent out their newfound skills. Far too rarely does a competence centre emerge.
- application architects (for in-house and packaged apps) often forget the requirement for data migration into their whizzy new systems. Nearly twenty years after it was first released, Oracle Apps still doesn't have a fully supported bulk migration solution for even the most basic data (eg Payables 11.5.10 finally added vendors, sites and contacts but still doesn't support their bank accounts...). What's unglamourous for the end user is equally unglamourous for the product developer, it seems.
Ho ho ho! Happy Christmas everyone