8 Smart Ways To Use Prescriptive Analytics - InformationWeek

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6/28/2016
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Lisa Morgan
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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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Recognize It's A Journey 
Many organizations have added predictive analytics tools to their arsenal after realizing descriptive analytics can only take them so far. What's the difference? Descriptive analytics tools examine business through the rear-view mirror. Predictive analytics can provide a probable view of the future, but users don't always know what action to take. Prescriptive analytics software takes it one step further, offering up action items and potential outcomes.   
'Predictive analytics -- the ability to predict outcomes days, weeks, or months in advance - is getting to be table stakes,' said Doug Henschen, vice president and principal analyst at Constellation Research,  in an interview. 'Prescriptive analytics - the ability to make recommendations or take actions to drive desired outcomes -- is the next step in the road toward analytical maturity. It's not a pervasive capability at this point, but the rise of data-driven insights and [decision-making] is moving many organizations and industries in this direction.'
The higher the cost of a transaction (or the higher the cost of a failure or compliance problem), the more likely one is to see prescriptive analytics tools brought in, Henschen said. That's why it's being applied in industries such as healthcare, life sciences, and financial services.   
(Image: Unsplash via Pixabay)

Recognize It's A Journey

Many organizations have added predictive analytics tools to their arsenal after realizing descriptive analytics can only take them so far. What's the difference? Descriptive analytics tools examine business through the rear-view mirror. Predictive analytics can provide a probable view of the future, but users don't always know what action to take. Prescriptive analytics software takes it one step further, offering up action items and potential outcomes.

"Predictive analytics -- the ability to predict outcomes days, weeks, or months in advance is getting to be table stakes," said Doug Henschen, vice president and principal analyst at Constellation Research, in an interview. "Prescriptive analytics the ability to make recommendations or take actions to drive desired outcomes -- is the next step in the road toward analytical maturity. It's not a pervasive capability at this point, but the rise of data-driven insights and [decision-making] is moving many organizations and industries in this direction."

The higher the cost of a transaction (or the higher the cost of a failure or compliance problem), the more likely one is to see prescriptive analytics tools brought in, Henschen said. That's why it's being applied in industries such as healthcare, life sciences, and financial services.

(Image: Unsplash via Pixabay)

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LisaMorgan
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LisaMorgan,
User Rank: Moderator
7/8/2016 | 4:23:17 PM
Re: Prescriptive analytics: A thought experiment
I worry about the accuracy of prescriptive analytics too because I think the problem is being oversimplified in a lot of cases.
LisaMorgan
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LisaMorgan,
User Rank: Moderator
7/8/2016 | 4:15:31 PM
Re: Prescriptive analytics: A thought experiment
Thanks for mentioning it.
GaryB790
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GaryB790,
User Rank: Strategist
7/5/2016 | 11:05:30 AM
Re: Prescriptive analytics: A thought experiment
@StevenL530,

I think that you may have missed some information somewhere. The Prescriptive Analytics data is not generated in a vacuum and the data is not static it is a function of accumulated data over some time period.  If need be, there could be a [pick your time frame] window to ensure that the trending isn't under reported by having a massive dataset showing the opposite of what is actually happenning.

Within the Prescriptive Analytics algorithm there should be a "feedback loop"...for example, page hits, or some socitial trending information gathered from somewhere else noting the trending of deserts, sweetners (artificial vs natural), baked or fried or frozed....etc.

Like all prediction algorithms, it takes time [for data sample collection] for the algrithm to optimize and predictive type formulation....and the correct data being sampled.
SteveR329
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SteveR329,
User Rank: Apprentice
6/29/2016 | 6:26:29 PM
A journey not an event
Great article.  I agree with most points.  Data normalization is critical (garbage in, garbage out) as is the human factor.  People are fickle which makes trying to predict the decisions they will make a very big challenge.  It is still a journey worth taking, but as you point out, expect it to be a journey not an event.
StevenL530
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StevenL530,
User Rank: Strategist
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.
ShannonK584
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ShannonK584,
User Rank: Apprentice
6/28/2016 | 1:53:15 PM
A bit of a limited review of the potential of prescriptive
Many points brought up here are valid. However, I worry that the view of potential use cases / growth with prescriptive are quite limited to the idea of heuristics (rules-based) decision automation that people (including Gartner) are incorrectly calling prescriptive analytics. 

If you view prescriptive analytics as optimization (linear programming), the use cases and benefit are much wider reaching. Also, you don't run into the probably of having misinformation from prescriptive (e.g., infeasible plans or plans that are not optimized to your business objectives). 

I recommend reviewing this article and considering redefining your idea of "prescriptive analytics." The use cases and benefits of what you refer to here are quite different from the use cases and benefits of true optimization. Furthermore, there are far fewer problems, and the benefits make attacking change management issues a no-brainer.
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