What is the Biggest Misconception About Big Data?

Data Informed recently asked Pete Eppele, and a handful of other data experts, one simple question: What is the biggest misconception about big data? Pete’s response:

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“From my perspective, the biggest misconception is that there’s more benefit and better ROI available from simple analytics on big data than from more sophisticated, predictive analytics on little(r) data. Managers often think that the next wave of benefit from data-driven decision making comes from amassing and analyzing a huge volume of data from a variety of different internal and external sources. They then start down the path of applying simple analytics to the data set to see what sales or marketing insights they can glean. Simple analytics, particularly when they are backward looking in nature and don’t have the ability to separate true signal from noise, can be confusing and, worse yet, misleading.

Regardless of how large and diverse a data set used in the analysis, simple analytics fail to provide a clear path forward for how to make better decisions in the future. A better approach is to start with the business problem in mind, seek out only the data you need to address it and apply sophisticated predictive and prescriptive analytics to the data. For example, a company’s transaction data that is collected in the course of doing business holds a wealth of signals that can inform everything from inventory decisions to pricing decisions to sales decisions when sophisticated analytics are applied to the data set. The output of those sophisticated analytics is not charts and reports that require interpretation. Rather, the output is forward-looking guidance to make a specific type of decision. This approach offers significantly more benefit at a much lower cost.”

Read the four additional answers in the full article.

Speak Your Mind: What is the Biggest Misconception About Big Data?

Price Elasticity Hasn’t Snapped, It Has Evolved

In this post, a new contributor to The Zilliant Blog shares his perspective on why price elasticity hasn’t snapped, but rather evolved. And how, with the aid of experts and a highly-sophisticated model, companies can predict the outcome of price changes before putting them into the market.

scottchan

Recently, an article published by Strategy & Business caught my eye, “Price Elasticity Has Snapped.” In it, author James Walker makes the claim that price elasticity is obsolete. For someone like myself, who designs and deploys science-based technologies that calculate price elasticity, the statement was shocking!

Intrigued, I read on and found that he was referring to the basic econ textbook price elasticity model. As in, if the price elasticity ratio is -5, then a 10 percent cut in overall prices would increase sales volume by 50 percent. His argument here is that “pricing models need to do more than predict sales volume.” On that point, I concur. In fact, I would further that point and say that yes, price elasticity is a complicated concept and should be treated as such, but it should not be thrown out or left behind. On the contrary, it should be addressed with even more rigor and handed over to experts to coax out the very best it has to offer.

Simple Elasticity Isn’t Enough

It is naive to just declare that elasticity has a value of five, and then expect the overly-simplistic model to perfectly predict price response and the resulting revenue/volume changes. As the author pointed out, there is a wide variety of factors that contribute to what will happen when prices change for which the model should account. The model must also account for cost, business strategies, competition, seasonality, lifecycle mixes and market prices, in addition to elasticities. Recommended prices have to become sufficiently granular, down to the deal level, accounting for customer, product and geographic deal attributes. In each deal circumstance, not only should the sales rep have the price in-hand that’s most likely to win the business, but also deal envelope prices representing the start and the floor of the deal which would maximize the company’s revenue or profitability goals. [Read more...]

Sales Effectiveness: Four Must-Have Calendar Blocks

By Cindy G. Goldsberry

Cindy G. Goldsberry is the author of ZFactor Sales Accelerator: From Vendor to Value Creator, which has been listed on Amazon’s Best Sellers for sales teams.

Cindy G. Goldsberry

Cindy G. Goldsberry

I was chatting with a client of mine on sales effectiveness tactics and she shared a breakthrough moment she recently experienced. One day, after 11 years of non-stop action in sales, she asked someone to answer her phone calls while she closed her office door for 90 minutes of uninterrupted activity. She confessed it was liberating to actually block off time to take care of some much-needed tasks.

In the nonstop life of a sales person, pausing the constant volley of emails and calls to complete actual work is nearly impossible. We think we are being efficient when we multitask, but in reality, we are not. Take Daniel Levitin, neurologist and author of “The Organized Mind,” in his recent interview with Radio Boston:

“It turns out that we think we’re multitasking, but we’re not. The brain is sequential tasking, we flit from one thought to the next very, very rapidly, giving us the illusion that what we’re doing is doing all these things at once. But I’m here to tell you, as a neuroscientist, just because we think we’re doing something doesn’t mean we are. Our brains are very, very good at self-delusion…What happens is, it releases the stress hormone, cortisol, in the brain which leads to foggy thinking, so you’re not even able to judge well whether you’re working well or not. It’s sort of like the way drinking can cloud your perception of whether you’re a good driver or not.”

Wow! More confirmation from the scientific community that multitasking isn’t an effective use of time. And when it comes to sales effectiveness, I believe that productivity can actually increase when sales reps discipline themselves to set times of hyper-focus. For example, I block recurring time each week for four tasks. Then, I type my to-do list directly into the meeting block so that my time is actionable as well.

Here are the four blocks of time I set on my calendar each and every week: [Read more...]