Image of engine. Photo by Garett Mizunaka on Unsplash

A good way to understand the impact of poor data practices on your organisation is to imagine the approach to data gathering, storage and exploitation as a machine – a data machine.

  • What does your data machine look like?
  • How well does it work?
  • Is it a high performing machine?

Read on to find out more…

Large machines, like large organisations, are complex combining many parts, components and systems to deliver required outputs. A well designed, built and operated machine will be productive for many years. Similarly, an effective data machine of people, processes, data and systems will deliver organisational objectives. Being ‘finely tuned’ will exceed the required outputs, efficiency and profit required by the organisation.

If all these parts do not align properly, if there are DIY parts (such as user created spreadsheets) then this data machine will be perform poorly.

We can characterise data machines in a number of ways…

Powerful machines

Excavator

Your organisation has perhaps spent significant time, effort and budget implementing a ‘best of breed’ enterprise system storing and exploiting your data. This data machine is comparable to an excavator in a quarry – robust, powerful and rugged that, if looked after correctly, will work efficiently for many years.

If you have recently implemented this software, your Exec will be pushing to deliver the intended benefits. They will also expect this data machine, like the excavator, to be robust, powerful and reliable for many years.

Does this represent the data machine for your organisation?

High performance machines

Racing car on a track

Alternatively, your organisation may be using agile methodologies to rapidly develop solutions and deliver required outcomes. This data machine will develop rapidly to support the organisation.

Similar to Formula 1 cars being ‘tuned’ for each race and having changes made between races. New iterations of the car are developed each season. Your Exec will be expecting there always to be a high performing data machine, like the racing car – high performing, flexible and ‘winning’.

Is your data machine high performing and flexible (and ‘winning’)?

Chaotic machines?

Tangled wires on a telegraph pole

Most organisations run on a complex mix of enterprise systems, specialist applications and legacy systems requiring many processes and data feeds between them. The interfaces between systems may not all work correctly needing manual ‘work arounds’ to feed data from one system to another.

There may be many spreadsheets and other user developed tools delivering new requirements or missing functionality. Your approach to master data and reporting may require significant effort to copy data between systems to create regular performance reports and dashboards for your management teams.

Does this sound familiar?

Like the image above, this tangle of functionality, processes, data feeds and interfaces will be inefficient. Extra effort or errors in processing will make it increasingly difficult to understand the ‘data machine’ of the organisation. Strategic decision making will be ineffective if data is poor. As mentioned in a previous post, all these inefficiencies reduce the profitability and effectiveness of the organisation.

Perhaps the way your organisation ‘does data’ is so haphazard and poorly defined that it can scarcely be thought of as a machine, never mind a high performance machine.

Tuning your data machine

Perhaps you are unsure how efficient and effective your data machine is? Perhaps you know specific areas where improvements are needed? What can you do about it?

We can support the tuning of your data machine by:

  • Identifying inefficiencies and problem areas
    • A data management maturity assessment provides objective assessment of your organisations strengths and weaknesses
    • Reviewing processes and system architectures will identify areas of inefficiency
    • Assessing data quality to identify the consequences of problems. Analysis of root causes to identify what needs improving
  • Recommending good practice approaches to improve the tuning of your data machine
  • Supporting implementation of changes
    • Implementing suitable data governance
    • Provision of Critical Friend support to increase competence and deliver improvements
    • Refinement and agreement of data requirements
    • Delivery of training
    • Development of data communities and communication to all business users

Are you ready to tune your data machine? Get in contact to start the process.

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