Can Machine Learning Provide Your Business a Competitive Edge?

Can machine learning give your organization a competitive advantage?Can machine learning give your organization a competitive advantage?

How can machine learning (ML) provide your business with a competitive edge today, and market leadership over time? When I attend technology conferences I ask my clients what they want to learn more about. Every year, I take this information and help them grow their markets, revenue, and profits. I’ve been doing this for many years.

This year I was invited by IBM to attend Think 2018 as their guest. I will be doing a series of onsite interviews and articles, both during and after the event. They pay for my conference ticket, meals, travel, and hotel for the conference. They set up meetings for me with key executives and thought leaders in business and technology. There are no other conditions they set for me being at the event.

Now If I could get my clients to be as flexible while I’m there. They see it as an opportunity to learn what other successful companies are doing. They know I don’t require much sleep.

This year an odd thing happened when I shared that I would be going to Think 2018. I asked my clients what they wanted me to focus on. Over 90% want to learn more about data science and machine learning. The common questions they asked included: How can these emerging business capabilities be used to grow their revenue, market share, and profits?  Which organizations are currently using machine learning and data science to find new opportunities and anticipate competitors’ actions?  Simple, right.

Here are additional questions on machine learning I’m taking with me to Las Vegas next week. If you have additional questions, feel free to send me an email and I’ll work to get you an answer.

My clients’ questions are not very technical, they go straight to the heart of business growth, seizing new opportunities, and finding long-term business success.  These clients are CXOs and line of business general managers. These questions have been put together over the past 60 days. They focus on how to leverage and accelerate adoption of this emerging capability!

Can ML help me better understand what customers value? How can it help me optimize my customer’s journey and experience? What does it mean for future product and service offerings?

Can machine learning help me create better products and services for my best customers and clients? Can it tell me which products I should keep and which I should discontinue producing?

Will machine learning help me leverage my own customer data in ways that impact revenue and profitability? Can it help us identify new opportunities for growth and revenue? Do I have to buy additional data to have the greatest impact on my data science initiatives?

How will machine learning impact my organization’s agility? Can machine learning help me create a more Anticipatory Organization?

How can machine learning help me capitalize on both hard and soft trends? Can it allow me to leverage soft trends to create a unique value proposition in my markets?

What role does machine learning have in both short opportunity identification and long-term planning processes? Can it help me identify the best partners in the sales channel for specific products and services?

Can machine learning help me decide where to invest my resources in developing new strategic partnerships across my business ecosystem?

Can ML help me control risk and increase upside in the new opportunities were pursuing?

Where should I invest my data science budget to get the best ROI? What role does machine learning have in keeping my technology spend in line?

What hard and soft trends are going to impact the cost and usage of machine learning over the next five years? Is there really of shortage of data scientists? What can I do about it?

How can I leverage machine learning to build a more effective data science team?  Who are the best members for my new, emerging data science team?

What companies are currently leveraging machine learning processes and systems? Which competitors? What is their ROI?

What are the best practices of a machine learning program? What are the key elements of a successful early ML adoption process?

Should I be outsourcing my data science and machine learning efforts? Why, and why not?

So many great questions, so little time. I’d like to thank my clients who contributed questions and budget to ensure I get my two hours of sleep a night! See you from Las Vegas next week at IBM Think 2018  I’ll be back here in two weeks. See you then.

About the Author

Tripp Braden partners with financial and advisory services clients to create an anticipatory strategy and mindset. By leveraging people and technology he breaks down barriers to combine planning and innovation in a way that increases profits and accelerates sales results.
He’s a growth strategist and internationally recognized Sage Global Business Expert and IBM Futurist who turns strategy into implementable business development activities for increasing market share, revenue, and profits. He has proven success seeing the big picture and creating new market opportunities.
Tripp can be contacted at tbraden@marketleadership.net or send him an invite on LinkedIn. You can find Tripp’s other blog at Market Leadership Journal.

Tripp Braden – who has written posts on Developing High Performing Teams.


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