Comments
View Comments: Newest First | Oldest First | Threaded View
Page 1 / 4   >   >>
SaneIT
User Rank
Data Doctor
Re: Asking the question first
SaneIT   9/4/2014 7:27:59 AM
NO RATINGS
@Jim.  That makes a lot of sense from the manufacturing side.  I wouldn't expect them to increase output but do agree that they could work with retailers to shift inventory around.  There are a few companies I know of that do just in time delivery for their manufacturing needs, why not just in time delivery for products like this.  I know you don't want to be driving trucks into a hurricane but having them staged a state away and ready to roll in from a safe distance would put products into a store about the time that people are finally coming out of their hiding places.

BethSchultz
User Rank
Blogger
Re: Asking the question first
BethSchultz   9/3/2014 4:37:11 PM
NO RATINGS
Jim, excellent points on the staging and great example of smart leadership on the Coast Guard's part. And, regarding that staging, location analytics could certainly be used to help determine the best spots for ease of access, proximity of storm path, etc.

Jamescon
User Rank
Editor
Re: Asking the question first
Jamescon   9/3/2014 9:51:28 AM
NO RATINGS
@Beth. Interesting point about manufacturers sending more generators to a region that is prepping for a hurricane. They probably couldn't justify ramping up production of a costly and complex item like that. However, they could work with their distributors to collect generators from parts of the country that aren't in the hurricane's path, and then ship them to the target area or at least a staging area. The manufacturer can then assure the distributors that if there's a real need for those generators the manufacturer can ramp up production to backfill in the stores that gave up their inventory.

Predicting demand for emergency resources in the face of weather is tricky. If you send all your equipment, people or inventory (generators) in too early they could end up being unusable because they are in the middle of the chaos.

The US Coast Guard got a lot of credit for their helicopter rescues on the Gulf Coast when Katrina hit. Other emergency agencies were helpless because they were on the ground in New Orleans and became isolated by the storm themselves. What the Coast Guard commanders did was smart. They shifted most of their East Coast and Midwest helicopters to the southern states, near the frindge of Katrina's path.

When the storm hit, the copters were safe and ready to go and only had the last few hundred miles to reach the scene and save lives.

The data can tell you where the weather is likely to hit and the resources you are most likely to need. Then good judgment by leaders comes into play, working off that data.

 

BethSchultz
User Rank
Blogger
Re: Asking the question first
BethSchultz   9/3/2014 8:31:16 AM
NO RATINGS
@SaneIT, I don't think you have to make too strong an argument to include weather intelligence in data-driven decision making these days. To your power-generator example, I'd add that it's not only the retail industry that needs to be paying attention but the manufacturers, too. In your example, manufacturers of power generators could have used weather intelligence to increase their sales into the region. Who knows, perhaps both the retailers and manufacturers could have benefited from getting utility data as well. Would the grid fail? Where were the most likely spots to have downed power lines? Where would it be most difficult for the power companies to restore service? 

SaneIT
User Rank
Data Doctor
Re: Asking the question first
SaneIT   9/3/2014 7:17:49 AM
NO RATINGS
The Sears example is a good one.  I won't go with rakes but let's go with something I ran into issues with a number of years ago.  When the first hurricane hit the area in more than 20 years there was a run on portable generators.  Had any retailer done 5 minutes of looking at shifting inventory they could have sold thousands of generators, instead I saw people going out of state to get them.  I have family that happened to be out of state when the storms hit so I had them pick up a generator for me on their way home.  Instead of looking at what sells and where the price's break point is they need to start looking at external influences.  I'm sure it affects many more things than seasonal hardware.  If I had to guess I would say that during bad weather more people ride the bus than walk for short inner-city transportation.  The same would go for the brutally hot days around here.  I'm sure more people walk in the fall and spring than in the middle of the summer.

BethSchultz
User Rank
Blogger
Re: Asking the question first
BethSchultz   9/2/2014 2:24:02 PM
NO RATINGS
@SaneIT, I agree that overly broad questions are a waste of effort and show little recognition of the power of analytics and the value that comes with it. I recall hearing a data scientist from Sears saying in a conference presentation how one of the biggest challenges his team faced when migrating from traditional data environmen to big data was getting the business users to change how they thought about what questions to ask. Everybody is used to thinking about questions like, "How many rakes did we sell last fall, and at what price?" and "How much revenue did we generate from those sales?" But with big data, they can ask a question like, "Last fall, at what price didn't our rakes sell?" The more thought that goes into formulating the question you'd like answered, the better off everybody will be.

 

 

SaneIT
User Rank
Data Doctor
Re: Asking the question first
SaneIT   9/2/2014 7:43:52 AM
NO RATINGS
I think too often the questions being asked are so general that they don't take advantage of the data collected or it puts undue burden on the data.  Asking questions like "how do we improve a process" is so open ended that anyone looking at the data is going to have a number of points that they could start at but they may not be able to tell which is the most sensitive.  There needs to be a little thought put into what is being asked for so that you get meaningful answers.

BethSchultz
User Rank
Blogger
Re: Asking the question first
BethSchultz   9/1/2014 9:52:02 PM
NO RATINGS
@Waqas, the trick is getting business users to think outside the box when it comes to the questions that want to answer. They might be surprised to discover that, yes, the analytics team can answer that question with the data the company or that it can't answer the question with the data it has but knows that if it brings in another data source, it could answer the question. The company can then weigh the potential gain from being able to answer the question against the cost of acquiring the data.

WaqasAltaf
User Rank
Data Doctor
Re: Hidden opportunities
WaqasAltaf   8/31/2014 3:53:23 PM
NO RATINGS
Pierre, that would be great if apps can be the means to communicate problems to governments. However, the apps need to be taken seriously by the government as well. If they aren't taken seriously, then even the best designed app cannot serve any purpose.

WaqasAltaf
User Rank
Data Doctor
Re: Hidden opportunities
WaqasAltaf   8/31/2014 3:40:40 PM
NO RATINGS
Pierre, in your opinion or experiences, do the IT managers/CIOs themselves reject proposals or demands of the users or the fights leads to senior management for resolution ?

Page 1 / 4   >   >>


Latest Blogs
Visualizations help communicate the meaning behind analytics to a variety of users. Now virtual reality is taking that a step further.
You've heard all about the data science talent gap that McKinsey cited in 2011, but there's a lot more -- including new information -- that you need to know about McKinsey's ongoing research. Learn more Thursday on All Analytics Radio.
What hybrid automobile offers the highest MPG? It's not the Prius anymore. Take a look at these visualizations to find out the new leader.
Understanding retail customers means knowing what they will want and when they will want it. To deliver that, retailers must be able to see customer behavior across physical stores, the web, mobile apps, and more.
Chatbots, AI, virtual reality, machine learning, and more will be featured as leading edge technologies for retailers attending the NRF Annual Convention and Expo in New York City. But many retailers are still getting their arms around advanced analytics.
Radio Show
A2 Conversations
ARCHIVE
Jessica Davis
Analytics: Make the Most of Data's Potential in 2017


1/19/2017  LISTEN   19
ARCHIVE
Jessica Davis
A2 Radio: Can You Trust Your Data?


12/20/2016  LISTEN   70
ARCHIVE
James M. Connolly
Retail Analytics: See Where Style Meets Statistics


12/6/2016  LISTEN   53
ARCHIVE
James M. Connolly
Why the IoT Matters to Your Business


11/29/2016  LISTEN   45
ARCHIVE
James M. Connolly
Will Data and Humans Become Friends in 2017?


11/22/2016  LISTEN   40
ARCHIVE
James M. Connolly
We Can Build Smarter Cities


10/20/2016  LISTEN   31
ARCHIVE
James M. Connolly
Visualization: Let Your Data Speak


10/13/2016  LISTEN   70
ARCHIVE
James M. Connolly
How Colleges and Tech Are Grooming Analytics Talent


9/7/2016  LISTEN   56
ARCHIVE
James M. Connolly
How Machine Learning Takes Handwriting Recognition to New Levels


8/25/2016  LISTEN   40
ARCHIVE
AllAnalytics
A Look at Tomorrow's Data Scientist


8/9/2016  LISTEN   83
Information Resources
Quick Poll
Quick Poll
About Us  |  Contact Us  |  Help  |  Register  |  Twitter  |  Facebook  |  RSS