The Analytics Enterprise
Beyond the competency centre
Building a team of skills analytics professions is relatively easy. You just have to train them in a range of analytics and visualisation tools - or let them choose their own - and then give then access to as much data as possible.
If you build an analytics team in this way you will have some success. Once people realise they can engage with this team to develop reports, and dashboards, and provide data to regulators, and provide data to the executive team, they will come from far and wide to make requests.
Faced with a broad range of stakeholders in different business units, and with access to more data than they can understand, the analytics team will reach a crisis point. The team will have more work than they can handle, for starters. They will also be doing a lot of work that isn’t “real analytics”.
Because they are some of the heaviest users of data in the entire organisation they will be handling data that nobody else does. This means it’s not well integrated, has poor quality, and doesn’t interoperate well with other data sets. Also, when people come to them for help it’s never because things are easy - the analytics team will by definition get the difficult tasks.
The commonly quoted statistics about the amount of time analytics team spend in data preparation a result of this approach to shift difficult and unsupported activities to the analytics team. This is also the reason why analytics teams have to service data requests, reports (rather then a “real analytics”) and all sorts of ad hoc activity.
At the same time, centralised analytics teams are the exception to many IT policies and service management processes, as well having unique support requirements. Every time the organisation tries to strength the protection of their data it makes it harder for analytics teams to get the data they need to do their job. Every time the IT team try to become more “agile” it becomes more difficult for the analytics team to understand where to get the data they need, or even what data is available.
Some analytics teams are left with the job of explaining why “the business” needs certain information - and then treated like “for analytics” isn’t a sufficient answer.
So building an analytics competency centre - once the key challenge in improving an organisation’s analytics maturity - is now the cause of modern organisational woes relating to analytics.
Analytics is the elevator
We have flattened our organisations over the last quarter century - but they still have at least three distinct layers of structure. The flattening of our organisations was always a follow on impact from the increase in peer-to-peer direct, direct, unbounded communication between all individuals, layers, and business units.
If you picture an organisation with three layers you have the executive layer on the top, a management layer in the middle, and an operations layer at the bottom. Even this view of the organisation itself is challenged by those who seek to make our organisations for customer oriented - so should be supplemented by a customer orientation that cuts through all layers at will.
Analytics teams are often challenged to make their analysis more business focused, simpler, more relevant. Using only data, the right analytics and visualisation tools, and an understanding of the decisions that might be made from the analysis - these teams are challenged to do what every other team can’t.
Analytics, when don’t well, traverses all three layers of the organisation, as well as incorporating the customer perspective. Just imagine all of the effort expended to keep those layers in place: executive teams doing anything they can to delegate work to management, management leaving the technical details to others lest they be accused of micro-managing, customer service teams compensating for broken back-end processes with work around some to maintain a positive customer experience.
Analytics, when it success, is cutting through all of that. It is selecting the right data from across operations to create a body of facts and evidence to underpin it’s analysis. It is ensuring that the information is summarised and presented in a way that management can deem as “actionable”, it is including the customer perspective to provide a lens of value across all analysis, and it is balancing this with the often functional, and siloed structure of most executive teams.