In this series of Blog posts I shall be introducing the ‘data management staircase’, what it means and the necessary journey over time to climb the steps to becoming ‘Excellent’.
Introducing the data management maturity staircase
Julian Schwarzenbach guests on the 30th episode of The Data Strategy Show
Julian Schwarzenbach recently appeared on the 30th episode of The Data Strategy Show. The conversation with Samir Sharma covered a wide range of topics including:
- Julian’s background in engineering and data
- The strapline “Data Doesn’t have to be difficult”
- Why we are still talking about Data Quality
- How business functions need to take responsibility for their data and data governance activities
- Julian’s approach to valuing data
- His book: Managing Data Quality: A Practical Guide and the idea of the “Data Zoo”
- The new British Standards he has launched around big data.
- The work he does at the British Computer Society
Why asset data is more challenging than ‘normal data’?
Increasingly, organisations are recognising the importance of good data management and how it can improve organisational performance. Managing data across large (and small) enterprises can be challenging, there are a range of standards and approaches that provide guidance applicable to many sectors.
Asset intensive organisations include refineries, power stations, substations, railways, water treatment and distribution networks, highways etc. Asset owning organisations typically have large portfolios of assets with huge variety of types, construction and configuration, ages, condition and performance. Such organisations need to manage their complex portfolio of assets over extended periods of time.
(more…)Why is data frequently stated as one of the top 3 challenges for asset intensive organisations?
What approaches to data work best for asset intensive organisations?
Is ‘IT’ or ‘the business’ responsible for data quality?
Most organisations have problems with their data – not enough, too much, not good enough, missing, duplicated, inconsistent etc. Many managers and employees just want someone to ‘sort it all out’, but who is responsible?
(more…)Often there is a view that data quality is IT’s problem, but is this correct?
Data quality assessment from an organisational perspective
Data quality assessments can provide large amounts of useful information. However, to gain a complete perspective on organisational data quality, it is essential to consider three key perspectives:
- The data itself – entries in databases and spreadsheets
- The requirements for data – arising from processes and organisational objectives
- The data subject – the person, product, activity or event represented by the data
Considering data quality from only one or two of these perspectives are insufficient to understand organisational data quality. Having a lot of information about some aspects of data quality may mask the fact that you are missing key data quality dimensions and insights. Activities to improve data quality may therefore not be correctly targeted.
(more…)The value of data
It is time to consider ‘the value of data’ – a number of recent conversations (such as with Stuart Ravens and Martin Paver), an excellent recent article on Highways England’s data valuation and related events such as the emergence of a proposed international standard to develop a ‘data value index’ show that this is a timely subject.
Symptoms of data quality problems
Do you have a data quality problem?
A recent conversation about a large organisation highlighted an interesting question – How do you quickly and easily know that you have got a data quality problem?
Clearly, you may have a data manager/ data team who are stating that data quality is poor/declining etc. But are they just obsessive-compulsive types who want everything perfect?
(more…)Two new data standards for all organisations
In February 2020, BSI released two new data related standards that should be considered by all organisations:
- BS 10102-1:2020 – Big data. Guidance on data-driven organizations
- BS 10102-2:2020 – Big data. Guidance on data-intensive projects
Although the titles state ‘Big data’, this only reflects the committee that created them. They are in fact applicable to virtually all organisations.
Read on to get an overview of what they contain
(more…)Start well….
There are two sayings that we will all have heard at some time:
- Start with the end in mind
- Start like you mean to go on
A client of ours demonstrates why these two sayings are important from a data perspective.
(more…)Has lockdown exposed your data weaknesses?
Staff can often be very resourceful in making poor systems and processes work and to overcome data problems within an organisation. If people are based in a single office then they can call out questions like:
- “Do you remember who did…”
- “How did we solve….”
- “Where is the information on….”
- And so on
I used to give a similar answer about why many smaller organisations were less affected by poor data quality than they would be if they were larger – namely, being close to colleagues and able to verbally resolve issues acts as a ‘sticking plaster’ to overcome data problems.
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