Risk Management & Data Analytics: Why Both Are Necessary
Risk management and data analytics go hand in hand towards achieving the goal of mitigating and resolving organisational risk. It’s not that they are two completely separate disciplines but rather that data analytics are a critical and necessary tool for meaningful success in risk management much like how analytics empower other departments such as marketing, sales, and more.
Consider for a moment that a successful manager of any business, big or small, cannot simply go off gut feelings about how well the business is doing. There’s something to be said for instinctual management skills, but an accountant cannot simply guess credits and debits to the books - no, accurate reporting and concise data, including analytics, give real meaning and insight to managers of all types. Risk management benefits greatly from analytics, but why are they really necessary?
Without data analytics, risk management would fail to consider the trends and root causes of effects within the organisation. Data analytics provide key insight into the contributing factors towards risks big and small that may have already been felt intuitively and bring to light those that may not have been initially considered.
There’s a massive difference between knee-jerk reactionary decision making and decisions made on thoroughly researched and investigated data. Managers that engage in the former fail to take into account the full reality of the situation and can cause more harm than good, such as by shutting down key operations due to a perceived risk rather than isolating its cause and having it dealt with appropriately without interrupting business processes.
Data Provides Benchmarking for Future Projects
Every time your organisation undertakes a future endeavour, you won’t have to reinvent the wheel when it comes to risk management processes. Naturally, every project should be looked at in isolation to an extent, so that specific risks pertaining to that project are identified.
Having a good backlog of projects which have used data analytics, however, can provide valuable insight towards future projects by showcasing similarities and thus eliminating time and effort since the new project may be comparable to an older one completed in the past.
With the consistent use of data analytics, everyone in the organisation will understand that their actions have real consequences on the success of the organisation, brand reputation, and more. Simply having data collection methods in place can motivate employees to engage in professional and accountable behaviour since they know that any risks arising from their actions can be traced back.
This is also helpful in the event of an audit as the risk management team can present their findings and display that they have used due diligence through data analytics.
There’s always a chance that in the real world, projects that have been planned out properly can run over budget or over deadlines due to various factors. The key difference is that those organisations with data analytics in place are often better able to address specific issues as they arise rather than face a catastrophic cost overrun as the project nears completion, for example. This contributes to better cost accounting and responsible finances within the organisation.
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