8 Smart Ways To Use Prescriptive Analytics - InformationWeek

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6/28/2016
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8 Smart Ways To Use Prescriptive Analytics

Somewhere between blind faith and skepticism is the world of prescriptive analytics. Here, machine-generated action items and potential outcomes meet human decision-making. Finding the right balance between algorithms and common sense can be tricky, so consider these tips.
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Avoid Blind Faith 

Not all prescriptive analytics platforms and software are created alike, although it can sometimes be hard to tell the difference. Some options are broad, some narrow, and some have been training on certain types of data for considerably longer than others. Despite what a vendor may claim, don't simply buy software or a platform subscription and hope it's going to provide the magical answers out of the box to meet your unique business needs.
'There's a risk that a prescriptive system might be blind to your real challenges,' said Doug Henschen of Constellation Research. 'Does the system have a sufficiently holistic take on the dynamics of the decision?'
'For example, a prescriptive system might draw certain conclusions about customer spending patterns, or a propensity to buy certain goods, if the data is limited to their purchasing habits with a single retailer. If the view is broadened to include social sentiment, demographic and lifestyle information, and perhaps third-party data on spending with other retailers, the recommendations might be very different,' Henschen said.
(Image: DasWortgewand via Pixabay)

Avoid Blind Faith

Not all prescriptive analytics platforms and software are created alike, although it can sometimes be hard to tell the difference. Some options are broad, some narrow, and some have been training on certain types of data for considerably longer than others. Despite what a vendor may claim, don't simply buy software or a platform subscription and hope it's going to provide the magical answers out of the box to meet your unique business needs.

(Image: DasWortgewand via Pixabay)

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StevenL530
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StevenL530,
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6/29/2016 | 10:52:12 AM
Prescriptive analytics: A thought experiment
Your algorithm prescribes adding the Fruity Pebbles cheesecake recipe to your web content. The counter-intuitive recommendation is only counter-intuitive the first time. The recommendation now becomes intuitive, routine. So each year, in late spring, you run another recipe just like this, Cap'n Crunch Cupcakes, Fruit Loops Parfait, and so on. But something changes. One year, the recipe no longer garners clicks. Visits are down. Will the prescriptive algorithm double down on its advice, run more breakfast cereal no-bake recipes? Or will it detect the root of the new trend? If it is just telling me what to do and not why, how does the managing editor know when to change course and in which direction? With dozens of statistical models forecasting every possibility, how to choose? Weather prediction has been banging up against this challenge for over a century. In business, we are always on the hunt for the disruptive change. Not only will prescriptive analytics miss the disruptive change, it will reinforce management's reliance on these now misleading analytics far longer than they otherwise might.
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