Enterprise Data Maturity for SME’s – can it be done?

“A lot of people talk about the democratisation of data, or more specifically about how they can use Power Bi within organisations to democratise the use of data within an organisation by allowing teams to collaborate on reports to drive better business decisions.

However, I think people also overlook how the cloud can help democratise data by giving SME’s the same tools and power to consolidate and analyse data in a way that previously only enterprise organisations could.

Yet in a recent Gartner survey, 87.5% of respondents had low data and analytics maturity, with this figure being even higher for smaller sized organisations. Partially this is down to the traditional costs associated with technologies such as Data Warehouse or advanced Business Intelligence tools. However, with the advancements in cloud-based technologies, these solutions are now available at a fraction of the cost and arguable deliver more value as the quantity of data at an organisation’s disposal has increased.

So why is it that this gulf in data maturity still seems to exist? Technology can only go so far, and while we do have the ability to use Microsoft Azure as the platform to deliver these insights, we also need to look at what the wider data strategy is and how this can be aligned to business strategy to deliver better citizen, tenant, student or patient services.

Typically, there are two main strategies I see used by organisations when it comes to their data preparation and distribution: Ad-Hoc and Centralised/Governed.

Ad-Hoc

This is the model often taken by smaller organisations and in short it relies on individual people or business units to take responsibility for the cleansing, shaping and transforming of the data that they’re wanting.

This undoubtedly gives organisations the ability to be more agile whilst potentially working within their current resource capacity in the short term to allow them to start to use data for analytics quicker without having to bring in additional heads or processes.

However, there are some big drawbacks to this approach particularly as an organisation grows in size due to additional user error, inconsistent approaches and key-person dependency within specific business units or teams. Furthermore, as these different approaches are rarely documented or reviewed it often means best practices are not shared and therefore can be much less efficient. 

Centralised/Governed

I’m not advocating here that the data should only be made available to a central team or department, as I’m a firm believer that the value of data is unlocked when it’s visualised in an intuitive manner and shared with key individuals to empower their decision making. What I am advocating is having a centralised team or department who are responsible for the data preparation within an organisation, and own the responsibility for sourcing, preparing and making available all data for reporting and analytics use across the organisation while making sure it’s available at the right time to the right people.

This has many benefits including:

  • Greater utilisation and sharing of data modelling best practices.
  • Commonality of fields, definitions, processes and rules to ensure that the same method documented and applied throughout the organisation – reducing your key-man dependency.
  • Greater efficiency and scalability by following a consistent data modelling methodology to prioritise query performance and flexibility and allow individuals to get the answers to questions they want as quickly as possible.
  • Reduces the duplication of effort within your organisation.

The downside of this is that it often involves greater planning and preparation both in building the underlying systems and also in developing the processes to support the organisation. There is also a need for access to either in-house or delivery partner expertise in developing these systems, processes and often visualisations.

However, the benefits of taking this approach in the long term very much outweigh the additional time and planning required in the short term.

If you’d like to learn about how this is possible for your organisation, what benefits it brings and why taking this approach actually helps de-risk your organisation in times of uncertainty, please join me and Weelin Lim, who helped co-create this blog, for a live webinar on Wednesday 27 May at 2pm.

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Or alternatively, as always, if you’d like to speak to us to learn more about how you can build an effective data culture within your organisation, please feel free to reach out to  hello@phoenixs.co.uk or call us on 01904 562200.”

Ben Gannon – Data and AI Specialist, Phoenix Software