PredictiveEverywhere

Predicting Revenue Growth
See how data science teams turn data into insights, smart data products & better business outcomes
   8 years ago
#PredictiveEverywhereMitigate risk and fraudDiscuss how predictive modeling can significantly improve your fraud detection capabilities
IBM Analytics
Last question of the day : Question #7 : How can businesses make revenue-generating insights actionable?
IBM Analytics
Please post your closing comments and replies here
IBM Analytics
2 minutes to go .......
jameskobielus
Measure whether they actually contribute to revenue growth. Programmatize them with data-driven predictive models and decision automation. Evaluate, iterate, score, report, repeat.......
IBM Analytics
Question #3 : How can the combination of predictive analytics and big data help organizations gain a competitive advantage?
IBM Analytics
Please post your replies here
Lisa B
#Predictiveanalytics is about making actionable information out of #BigData
Jane Hendricks
It can help the manager @mikejulietbravo was talking about earlier -- #bedataconfident -- maybe?
IBM Analytics
Waiting for your comments!!
Mike Briercliffe
there is a posting lag on this platform :-)
Luciane Ellis
Predictive Analytics deliver insights from Big Data
Samirul Mallick
how about making #machinelearning #alogrithms more powerful and scalable such that a Datamodel or MLmodel can deliver the accurate results from unstructured data #predictiveeverywhere
Jane Hendricks
#predictiveanalytics is #analyticswithpurpose -- big data gives it the additional power and insight like sentiment analysis, geo spatial, and more
Mike Briercliffe
Key issue here is not only BIG data - but the sheer speed at which it appears
Ankita Asthana
using predictive analytics companies can use big data proactively ..lot of wht if problems can be solved using predictive techniques
jameskobielus
If you have a larger pool of historical, profile, transaction, & other customer data, you can build far more nuanced segmentation models and drive more accurate predict models regarding their propensity to churn, accept offers, etc
jameskobielus
Higher velocity of updates of customer data drives your ability to update your predictive model of what they might do next. That's a revenue-boosting advantage when you're driving next best offers.
Samirul Mallick
@mikejulietbravo agree so the challenge is with the scalability to handle the performance and manage the data
jameskobielus
Higher variety of customer data types (e.g., transactions, sentiment, clickstreams, social) can drive a more well-rounded predictive portrait of their propensities. Revenue-boosting advantages there too.
Jane Hendricks
Scale is key. Need to think scale from the beginning
Ankita Asthana
also the sheer volume of data #bigdata can be used to train #predictive models to be more accurate hence giving better results
Mike Briercliffe
Retail and Predictive is an easy concept to grasp: speed, volume, sentiment etc etc
jameskobielus
Higher volume of customer data--such as you gain from a deep historical record of their transactions and interactions--can help you develop and validate predictive models of them under diverse scenarios. Makes predictions more robust
Mike Briercliffe
B2B is a different paradigm
Mike Briercliffe
Gotta sign out - good chat so far :-)
IBM Analytics
Time for question #4 at the top of your screen
Rajagopal Senthil Kumar
big data is big win on massive dataset to capture modern art. But all modern art is not understandable. So it requires additional catalyst like machine learning+data scientst need to make it happen.
IBM Analytics
Question #6 : What skills and capabilities are needed to succeed with analytics?
IBM Analytics
Please post your replies here
Umut Şatır Gürbüz
Understanding the business, asking the right questions, ability to read the data, using correct techniques and successful deployment
Ankit Singh
out of box thinking... clear concept of basic
Rubens Zimbres
critical thinking, statistics, machine learning, knowledge of business domain, storytelling, programming language, creativity and understanding of customer needs (through research and analysis)
jameskobielus
To succeed with analytics, you need to understand what decisions might be improved with data, structured reports, visualizations, predictions, etc. And you need to deliver analytic insights to right decision makers at right times.
Luciane Ellis
You need a team with different capabilities and expertise.
jameskobielus
To succeed with analytics, you need a center of excellence that recruit, cultivates, and manages your skills, tools, and practices in data mining, predictive modeling, visualization, etc.
Deepak Seth
Astute Number-savvy Adaptable Listener Yeasty Tool-savvy Inquisitive Collaborative Speedy
jameskobielus
To succeed with analytics, you need to instill a passion for data-driven decision making into every level of the organization. It needs to be infused into your business culture.
Samirul Mallick
I think the capability to collaborate between expert #ML #Datascience #engineering team with #Sales and #marketing will help to achieve business goals by leveraging analytics :) #predictiveeverywhere
Deepak Seth
ANALYTICS :Astute Number-savvy Adaptable Listener Yeasty Tool-savvy Inquisitive Collaborative Speedy
Ankita Asthana
ability to look at the bigger picture, move from data processing to insight mining , having the best technologies/solutions to take care of your data and the ability to communicate the insights to all stakeholders
Lorena Gonzalez
Aske the right questions, know where to look, know what to look for, ability to contextualize data
Samirul Mallick
@jameskobielus Absolutely agree with you . Bang on !
Ankita Asthana
stakeholders buy-in in very important for organizations who really want to benefit from analytics
Lisa B
An adaptive analytical leadership with an enthusiasm for data who can think outside of the box and drive a team
Jane Hendricks
sometimes we neglect to consider culture. There needs to a culture of curiosity and trust in data for #predictiveanalytics to succeed
Luciane Ellis
A collaborative environment with technologies that can support different needs and capabilities of the team
Samirul Mallick
@jane_hendricks yes. it's also to do with growth mindset and be with solution oriented approach #predictiveeverywhere
IBM Analytics
Question #5 : How can the inability to forecast future events limit a company’s growth?
IBM Analytics
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Deepak Seth
"You're only as good as the future you foresee"!
Ankita Asthana
future gazing is now within reach for all and with the changing business dynamics and pressure to stay ahead, inability to forecast and be prepared for future is a must!
Luciane Ellis
Without the ability to forecat fututre events you keep working in the dark.
Jane Hendricks
It's not just forecast but forecast with confidence that's key. Anyone can guess at a future, #predictiveanalytics can #measurethefuture
jameskobielus
Inability to forecast demand means you risk not delivering sufficient amounts of the right kinds of products into the market to realize revenues when demand materializes. That's a predictive weakness that can doom any business.
Deepak Seth
Companies which do not foresee/predict the future so will feel the impact of what was actually an evolutionary process as if it was a "Big Bang".
Ankita Asthana
@jane_hendricks absolutely agree. #prediction needs to be #data driven not just based on intuition
Deepak Seth
Guys who see an oncoming bus and prepare for it can run alongside it a bit and then board it ; guys who are oblivious will be "hit by a bus".
jameskobielus
Inability to predict key events--e.g, customer retention, offer acceptances, etc.--means you may be missing out on "low hanging fruit" revenue opportunities.
Jane Hendricks
#data driven predictions give people an opinion-neutral starting point #beyondguesswork
Samirul Mallick
#machinelearning and #datascience have become important aspects of any org.without it there will be high risk of loosing competition,customer trust in a fast pace world.understanding customer choice is an important element of growth strategy
jameskobielus
Inability to predict how your competitors might respond to various marketplace conditions, including your own moves, means they might gain a strategic advantage over you.
Lisa B
By forecasting future events you can put the personnel, time and money where it is needed and stay ahead, the opposite becomes true if you don't have a forecast & #predictiveanalytics
Jane Hendricks
@sourcingpower yes there are too many data points available and without #predictiveanalytics you are likely to miss the answer that's right in front of you
IBM Analytics
Time for question #6 at the top of your screen..
jameskobielus
Inability to predict marketplace disruptors and other "black swans"--or at least to mitigate the risks of those "unforeseeables"--means you're strategically vulnerable, though you may in fact still be growing revenues.
Luciane Ellis
Inability to forecast can also increase costs and decrease revenue
Rubens Zimbres
Revenue depends upon sales, market segmentation, profit per unit and availability. Analytics allows us to quantify demand, do market segmentation and match market's needs. Without analytics we are back to the 90's.