Data Silos ? – Call an Expert


Recognise this ? Data silos everywhere. Disparate systems, and, seemingly, brick walls between them all. As our reliance on systems has grown, we have more of them to satisfy our business functions, and the integration problem becomes exponentially worse.

Consequences (1 – Internal)

The internal consequences of having data silos are serious, including overly costly processes, inaccurate information, duplicated records, and stifled collaboration.


Consequences (2 – External)

By far the worst consequence, however, is external. It’s about having no clear view of your customer. No “Single Customer View”. This is bad enough when you are trying to internally assess a given customer, but in a web and mobile enabled world, it often translates into the customer having partial data held in several different systems, and a completely disjointed and frustrating set of interactions.



Why it Happens

These silo’s propagate due to a number of factors, Mergers and Acquisitions, Departmental “Turf Wars”, lack of Strategic Vision, and more recently Cloud and Software-as-a-Service systems have become more ubiquitous, and have allowed departments to make their own purchase decisions, without enterprise oversight.


Many organisations rightly conclude that, rather than contemplate an impossibly risky “big bang” , where all systems are replaced, they need to migrate data into a place where it is more complete and coherent. Typically into an ERP, or CRM system, or data warehouse.

Having done this several times over the years, I’ve tended to call this process “Data Harmonisation”.


There are two fundamental aspects to this endeavour. The first (perhaps obviously) is some sort of technology platform to do the various data transformations/re-formats/matches etc. The second is expertise, and it’s this area which is often overlooked.

It is simply impossible to get good results by throwing technology at the problem. What’s needed is solid expertise around all-things-data. The whole nature of this endeavour is about bringing together data from differently structured databases, and performing complex things with that data.

It’s not just about re-formatting data, but also much more sophisticated processes, for example: identifying where there is a “match” (e.g. fuzzy matching of records from different systems where these might actually apply to the same customer).

As mere mortals, we understandably focus on the tangible stuff, so , the “system” is something we associate with the things we see on the screen, however, in a Data Harmonisation process, it’s actually the data and it’s structure which is vital. This is where data expertise is needed.


In my experience, this expertise is actually the primary determinant of whether a data harmonisation project will succeed, and NOT the technology platform which is chosen.

So I guess the message here is .. if you are looking down the barrel of a data harmonisation project .. then getting an expert is vital.

Blame Data for Bad Customer Service

I recently phoned my mobile operator with a query. I spoke to five different people, all of whom made me  quote my customer account number, and repeat the details of my query, which I can now do in my sleep.. (That was AFTER I’d diligently keyed my account number into their call-handling system.).

A few months earlier, I saw the CEO of the very same company speak, with passion and conviction, about putting the customer first. Sadly my experience was completely at odds with his intent.

But this isn’t about his sincerity, or that of the other people in the organisation.  It’s about disparate systems, processes and databases, each of which is responsible for a different part of the customer relationship.

This can often feel like unco-ordinated mayhem..

In my experience, the organisation in question is actually in the majority. The reality (and it’s a difficult one) is that to be truly ‘customer centric’, you need a single database which feeds all processes. Whilst I would never underestimate how difficult it is to adopt this ideal, it’s worth trying to go as far on the journey as possible, because every step will reduce innefficeincy, improve the customer experience, and so help the bottom line. If you don’t adopt a customer-centric philosophy, processes and systems can proliferate to the point of collapse,

Some call this Customer Data Integration (CDI),  or Master Data Management (MGM). I call it Data Harmonisation, because it involves taking many different  different inputs and orchestraing them towards a single, co-ordinated ensemble.

The nearer you get to a single customer database, the more duplication you drive out, and the more value you add.