With the potential of removing legacy IT silos and freeing up valuable data to gain greater insights into their operations, enterprises continue to invest heavily in analytics. Providing powerful analytics tools to business analysts who can get to work immediately on complex challenges instead of having to wait for ITs’ often over-committed resources is also …
Gartner, Inc. today said advanced analytics is a top business priority, fuelled by the need to make advanced analysis accessible to more users and broaden the insight into the business. Advanced analytics is the fastest-growing segment of the business intelligence (BI) and analytics software market and surpassed $1 billion in 2013.
With the potential of removing legacy IT silos and freeing up valuable data to gain greater insights into their operations, enterprises continue to invest heavily in analytics. Providing powerful analytics tools to business analysts who can get to work immediately on complex challenges instead of having to wait for ITs’ [...]
The truth is, companies must understand what they want before they go analyzing things helter skelter, especially when it comes to making predictions. He points out that there are really only four things businesses can use analytics to predict: risk, opportunity, fraud and demand.
The Second Trap: Starting at the Top
Operational decisions, such as those in which companies choose a supplier or determine whether to extend credit, lend themselves well to predictive analytics. So companies need to recognize that predictive analytics works best for prompting decisions about operations, rather than initiating their use
The Third Trap: Building Cottages, Not Factories
Focusing on decisions can help companies avoid another path to failure: creating analytic models that don’t scale. Analytics specialists are no more connected to the business than technology specialists, Taylor said; focusing on decisions can help bridge that gap. Otherwise, analytics specialists are prone to create the equivalent of a cottage industry, where the models built apply to only one thing, or are too complex and expensive to be reused easily.
The Fourth Trap: Seeking Purified Data
Taylor says good data is useful, of course, but companies should start with the business decision they want to make, and then look for data that might help them predict outcomes. Remember that the needed data may come from outside corporate walls. For many either/or business cases, the data you need might not have to be pristine.
Must read article from the excellent James Taylor. Key simple takeaway: "there are really only four things businesses can use analytics to predict: risk, opportunity, fraud and demand". (may be a few to add, however, for example linked to predictive maintenance in discrete manufacturing)
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