And Jerry Says : A Path to SUCCESS with Advanced Analytics


Folks, I am very proud and happy to have my dear friend Jerry Kurtz do a guest blog on my site. Jerry runs the Cognitive and Analytics businesses in my portfolio, and is a long time IBMer. He has been in this field for 30 years across SAP, Managed Business Process Services and Analytics and now Cognitive for last few years. He is a man of many talents outside work too – a very good singer – he is the lead singer of the “midlife crisis band”, a competitive golfer, and an overall good dude to hang out with. He lives with his wife Amy, his daughter Emily , Son Adam and his 3 year old fur kid Baxter, a Chocolate lab. You can find him on twitter as @jerry_kurtz 

Jerry with Fish

Take it away, Jerry !

I will start with sharing highlights of my beliefs regarding the “10 Fundamentals of Successful Advanced Analytics Programs”.  I hope to go deeper into each of the 10 in subsequent posts.  Also, for the purposes of this blog, I will not define each element of analytics.  Rather than keeping “predictive” separate from “optimization” and “prescriptive” separate from “cognitive”, let’s just call it all “Advanced Analytics”, shall we?  We shall…

Analytics Screens

Fundamental #1 – Establishing a “Balanced” Advanced Analytics Strategy. Any analytics strategy must have three basic things.  These three basic things may seem like “motherhood and apple pie” to some of you, but it’s amazing to see how many times we have seen Fortune 500 companies make mistakes on these basics.  More on case studies in future blogs.  Your analytics strategy MUST HAVE:

  1. A Business Capabilities or “Use Case” roadmap that answers the question “what solutions do we need to implement for our BUSINESS, USERS, and BUSINESS PARTNERS to achieve our business goals”? This is the value side of the equation.
  2. An Information Foundation roadmap that ALIGNS very tightly with the Business Capabilities roadmap. A strong data foundation does not in and of itself create value (with few exceptions), it ENABLES the full range of business capabilities and VALUE to be rolled out over time.  The above two strategies MUST be aligned with each other to maximize value.
  3. An Organization / Governance approach and roadmap that also aligns with overall business strategy and the above elements of the analytics strategy. We have seen that the “technology can be the easy part”. It is often the organizational structure, culture, and related politics that gets in the way of success.

Fundamental #2 – Establish a program goal of “10X value to cost” and “Self-funded”If you have the right level of executive sponsorship and you scope analytics programs properly, you can target at least $10 of hard value for every $1 of program cost.  Also, if you prioritize business capabilities the right way, self-funding is achievable within 90 days of program start. If your analytics strategy is not meeting these metrics, you should probably rethink your strategy.

Fundamental #3 – Think and Act with “Parallelism”Self-funded analytics programs can’t be achieved by working “serially”.  We have seen clients say, “we need to get our data fixed first, then do basic Business Intelligence and Reporting, THEN we will do some advanced analytics”.  In today’s world, however, parallelism is key. For example, some advanced analytics can help fund other elements of the program.  New business capabilities can help fund data transformation.

 Fundamental #4 – Having the right level of business sponsorship Without going into too much detail (yet) I will summarize my experience that the most successful analytics programs have senior and clear business sponsorship / ownership.  In the last couple years, my most successful analytics roadmap / implementation program was sponsored by the global CFO.  Just an example.

Fundamental #5 – Picking the right place to start  If you have 50 new innovative ideas for Advanced Analytics use cases, the best place to start is usually on use cases that (1) have strong executive sponsorship / business need, (2) have data readily available to solve the problem, even if in multiple sources, (3) LOW COST but HIGH VALUE for Phase 1 (e.g. Proof-of-Value).  Again, this may seem basic, but we see mistakes all the time.  Last year, I walked into a client that had started with a global management dashboard across 10 countries.  Very expensive and very time consuming.

Fundamental #6 – Scaling beyond science projects For now, let’s just say that the technology aspects and “finding smart people” will be the easy part.  The “soft stuff” will make or break the project.

Fundamental #7 – Embrace diversityI grew up in the ERP market where there was a fair amount of homogeneity across project resources e.g. similar background, similar training backgrounds, etc.  During my last several years in the Advanced Analytics space, I have met hundreds if not thousands of people, and I can best summarize them by saying that “they are all from different planets”.  While the incredible diversity in this space can make it much more difficult to assemble a “winning team”, I personally LOVE the challenge and so should you.

 Fundamental #8 – Teamwork / collaboration – At the risk of being too high level for now, I will summarize by saying that it’s all about resource “mix” including both mix of skills but also personality types.  For example, I would rather work with an A- data scientist who works well with others rather than an A+ data scientist who is always “the smartest person in the room”.

 Fundamental #9 – Analytics practitioners must be life-long learners e.g. “Adapt or Die”As Thomas Friedman explains in his recent book Thank You for Being Late, we have reached a point where technology is changing faster than humans are able to adapt. We and our teams had better keep up with rapid change or we risk becoming obsolete.  This challenge can only be overcome through life-long learning and constant, adaptive change.

 Fundamental #10 – Be Hands OnWe ALL need to find ways to be hands on with analytics technology.  If you are “only” a project leader or a business analyst or a practice leader, you should find ways to “sign-on” and learn your trade at a hands-on level.  Generalists with minimal technology savvy will struggle in the coming years, but “hands-on” specialists will thrive.

I hope you have enjoyed reading this as much as I have enjoyed writing it and sharing with you.

Thank you.

Jerry

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11 thoughts on “And Jerry Says : A Path to SUCCESS with Advanced Analytics

  1. Pingback: Terrific Practical 10 step path for success with Analytics from Jerry Kurz. – Thoughts, Theories, Facts, and Notions

  2. @Jerry : Nice reminder on getting started on the right foot with Analytics..IMO plunging into something new without a thought out strategy just because the competitors are doing it is a quick way to get started but can frustrate the team if enterprise risk tolerance is missing or adequate “aircover” is not provided by the champion. Great to see you featured on Vijay’s blog and it was nice to get a call from you the other day;-)

    @Vijay: I read your nice Watson rebuttal the other day- Keep Rocking buddy!

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  3. A nice list, Jerry. It reduces to a few key principles. You need to be published more broadly. Perhaps as a corollary to the Fundamental #8 Teamwork bullet, would suggest that bias toward taking shared ownership in the result is also fundamental for successful team dynamics.

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    • Thanks for the comments Mike. Great point. I was just in India last week with a project team that is scaling up to deliver a VERY large, global advanced analytics project for a client. We are not talking about POCs/Pilots, we are talking about a major program that is moving to production in many phases over a couple years. Team dynamics including shared mission/ownership is indeed critical and requires very careful evaluation on a regular basis. Little things can trigger broader issues/challenges, but it’s also so nice to see large team dynamics come together!

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  4. Nice. Like the way its split into fundamentals.
    I think the biggest challenge on advanced analytics is convincing the business benefits in terms of ROI ($$$) to the sponsorer

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    • Thanks Prashant. Fair point. I agree that ROI validation is critical and challenging at times. I am also a huge fan of picking the right use case(s) to start the advanced analytics journey. There’s both an art and a science to picking the right starter use cases.

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  5. Great write up Jerry!. The biggest hurdle I have heard from clients on Advanced Analytics projects is quantifying and later realizing the envisioned business value as organizations need to act upon the insights they are gathering. Program Governance and Executive Sponsorship hence have to play a larger role in defining the right performance measures to start with and in ensuring subsequent action and accountability in realizing the hard dollar savings.

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    • Thanks Sushanth. As I look at the various comments thus far, the big “theme” is that the combination of the right senior sponsorship and strong business case are both at the top of list of keys to success. As evidence of this, my team once did 17 (seventeen) advanced analytics POCs for a major client. ALL POCs were deemed very successful by the client stakeholders. However, the program did not continue / expand after this first batch of POCs. The main reason (with hindsight 20/20) is that the initiative had the incorrect sponsor to help wade thru the business side of the buy-in / politics. I will leave it at that for now…., but what a tremendous lesson learned! PS. “NO SCIENCE EXPERIMENTS” 🙂

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