​Big Data: The perils of improper use of analytics…

Analytics projects that utilise big data or advanced analytics are increasingly popular but present a heightened risk of failure.

It is the complexity of the analytical question to be addressed that drives the need for advanced analytic tools, and in many cases desired outcomes can be achieved without resorting to more sophisticated analysis.

Balancing analytic insight with the ability of the organisation to make use of the analysis

Because analytics can only be beneficial in organisations that are willing to embrace change, it makes sense to limit investment in analytics to a level that matches the organisation's ability to use the resulting insights.

Analytics may not be the most suitable approach:

•If pertinent data is absent

•When here are high levels of ambiguity

•Where there are entrenched opposing points of view

•In highly innovative or novel scenarios

Linden believes in these cases, scenario planning, options-based strategies, and critical thinking should also be incorporated into analytical approaches to better support the organisation's ability to take action.

Prioritising incremental improvements over business transformation

Using big data and advanced analytics to improve existing analyses, or to incrementally update and extend an existing business process, is easier than using them to deliver business transformation, because there are fewer dependencies to overcome to ensure success.

Care should be taken to validate the level of overall change required. In some cases, deep reform of the business strategy may still be necessary - for instance, when a new disruptive vendor enters a market, when technology innovation changes the business model, or when an organisation has become dysfunctional.

Considering alternative approaches to reaching the same goal

Few objectives can only be achieved in one way. Statistical modelling, data mining and machine learning algorithms all provide means of testing ideas and refining solution propositions.

Big data and advanced analytics help validate proposed hypotheses and open an even wider range of potential approaches to addressing corporate priorities.

Not all problems even require a fully engineered analytical solution. Investment may be better targeted on human factors, re-education or reframing the problem.

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