Data analytics helps to convert large quantities of data into relevant information – valuable insights - that can improve decision-making in your organisation. This also means that data analytics can have a direct impact on the implementation and communication of your organisational strategy.
After all, if you do not back up decision-making with good information provision, you can only rely on your gut feeling. Without overestimating the role of data analytics, it gives users the ability to corroborate and evaluate their gut instinct. Relying on one certainly need not rule out the other.
Availability, integrity and confidentiality
Traditional data analytics is characterised by a focus on numerical tallies - such as the number of customers, current stocks and production figures - at a given moment in time. While this is a useful exercise, it only tells you what has already happened.
In theory, organisations rely on pre-defined datasets. But in practice, analyses are largely compiled by extrapolating dumps from information systems in a spreadsheet. The systems supplying this data are often insufficiently integrated. Moreover, reports tend to be compiled manually, which makes them sensitive to error. They also lack a single source of truth, relying instead on more than one reality, depending on the system you consult.
A more contemporary information supply, by contrast, is characterised by high levels of availability, integrity and confidentiality. Master data is processed centrally, data catalogues are widely available and access to data is properly documented. Moreover, analyses are carried out on dedicated databases where data may or may not be anonymised.
Incorrect use of data analytics does more harm than good
The maturity of an organisation and its information supply has direct repercussions for the scope for analysis. Organisations with timely access to accurate data can use it almost immediately for analytical purposes. One analysis technique we use, for example, is process mining, which measures efficiency, identifies bottlenecks and establishes whether the process concerned complies with legislation and regulations. We also use machine learning (often confused with artificial intelligence) to detect anomalous transactions, thereby making techniques such as continuous control monitoring and management by exception more than just conceptual ideals.
Academic disciplines such as statistics and research philosophy are also increasingly finding their way into practice. Data analytics is a powerful tool, but can do more harm than good if used incorrectly. The results of research should contribute to better decision-making, but the reverse will happen if outcomes are based on erroneous assumptions, lack of sound methodologies and/or inaccurate conclusions.
Focus is shifting and technology is changing
In the near future, data analytics will focus much more on the outside world. As a result, organisations are likely to start combining their own data sources with external dataflows, partly on a freely accessible basis and partly in the form of charged services. And it is not only the improved computing power that will make other approaches possible, but also the way in which new, non-relational databases process data requests. That is why we expect the focus of analyses to shift to a more predictive and domain-specific approach.
And, last but not least, the way in which users acquire and above all process information will take on a more prominent role. We refer to this as the user experience: the interaction between the user and the product or service.
What can BDO do for you?
Our specialists would be happy to tell you more about data analytics in the context of digital transformation. We are ready to provide you with new perspectives on the opportunities that are available within your organisation.
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