Follow Gregory Piatetsky, No. 1 on LinkedIn Top Voices in Data Science & Analytics

KDnuggets Home » News » 2014 » Sep » Opinions, Interviews, Reports » Exclusive Interview: Imran Siddiqi, SAP on Why the Business needs Ambitious Big Data Use Cases ( 16:n16 )

Exclusive Interview: Imran Siddiqi, SAP on Why the Business needs Ambitious Big Data Use Cases


We discuss the selection and tracking of use cases, key points for designing a sustainable information architecture, the need for ambitious use cases, SAP's competitive differentiation, and more.



Imran SiddiqiImran P. Siddiqi is Senior Principal at SAP, where he advises executives on business value creation from technology innovation. He leads strategy engagements with executives, helping them use Advanced Analytics to gain a sustainable competitive advantage in their industry. In addition he is a thought leader and evangelist for big data analytics, writing practical guides for CMOs, CFOs, and the nascent Chief Analytics Officer roles.

Prior, Mr. Siddiqi was at CEB, a best practices research and analysis firm, where he held multiple roles including Senior Director of Strategic Marketing, Chief of Staff to the CEO, and Senior Director of Research. Prior to CEB, he held roles in strategy consulting at Bain & Company and at Kaiser Associates; he started his career in FP&A at Engro Corp.

Mr. Siddiqi is passionate about teaching and education, and is active in the community through nonprofit work, including serving on the Board of Directors of Ingenuity Prep, a charter school in Washington DC.

First part of interview.

Here is second and last part of my interview with him:

Anmol Rajpurohit: Q6. Identifying the Big Data use cases and quantifying the business value of those use cases is often not easy. What role can the Big Data vendors play in helping their clients with this?

Imran P. Siddiqi: Look at what your organization is already doing that could be improved – or what others in your peer group are doing that could be emulated. What could be done better with Big Data techniques, such as mashing up social data with product data, or developing new cost models based on consumer profiles? Ask your partners / vendors to give you a baseline portfolio of use cases, ranked by level of maturity – but make sure it is not a generic list. My team here at SAP, known as Industry Value Engineering (IVE) has developed this for different industries already and mapped each use case to a level of maturity. Big Data Value

The biggest challenge I see around use cases is figuring out the right portfolio of use cases, one that balances short term, quick win use cases, while building up grander “Big Hit” use cases that are much higher on the maturity spectrum – they may have longer lead times but they will deliver big value, often helping provide competitive advantage.

At SAP we do a lot of educating of our customers – and part of that is a service called the Big Data Strategy Engagement. It’s a systematic, collaborative way of surfacing the right use cases, benchmarking the maturity of your current and aspirational abilities, building a business case containing an ROI and also a storyline that answers the Why and the So What for the Board and leadership.

We build it in direct collaboration with customers in a simple 4-step process, and from our side we bring a team of strategists, design thinkers*, data scientists, technologists and architects. This helps our customers choose how they want to proceed, and then we can get into architecture, roadmaps and technology choices. Our goal is to help you craft a vision or if you already have one, to strengthen it and then accelerate it to make it real. If this sounds like a strategy consulting engagement to you, then you are correct – it is. However we do not charge for this service: we are in the software and cloud business and our goal is to help customers figure out how to capture value in their business using our platforms, solutions and expertise.

* Quick note about “Design Thinking” – it’s something that we leverage in addition to business thinking.

AR: Q7. What are the key considerations in the design and implementation of Information Architecture?

IPS: Don’t fall into the trap of diving into the specific tools you have or want without first thinking through the complete “logical” architecture you will need. Your use cases will be what drives what elements you need in each layer.

This is an important task that needs the right amount of time to do but most importantly it needs an objective Information Architecturelens. Depending on how you look at it there are as many as 9 layers to consider. We have a chart that shows the elements within each of these layers – and there are no product names on there, just what the element does. The readers interested in a quick assessment of their set up along these lines, can use the Big Data Architecture Assessment which is a quick check up – it’s available here

Disaggregating in this way helps to really understand what you need – and what you don’t. Most important, it also helps you later determine whether what you already have in-house is up to the task or not. Once you have done that and validated it with the stakeholders, then you can start to actually put names and logos in. This way, you know exactly what you need, and where the gaps are. Then you can more easily do a trade-off analysis of how best to fill those gaps. For our customers many of those gaps can be filled relatively easily because of the engines already built into SAP HANA, its connections with all kinds of data science packages, plus of course it’s an in-memory columnar database and with SAP Smart Data Access getting data in and out is not a problem anymore and so on.

The key to a sustainable information architecture is:
  • Few components to deliver current and future use cases
  • Pre-integrated interoperability
  • High degree of content and access security
  • Manageable with standard skills
  • High degree of performance
  • Centralized and accountable support with no blank areas (especially in integration points)
  • Deliver user centric solutions

 
AR: Q8. Help us understand your following statement: "Shareholder impact and value of Advanced Analytics grows with ambitiousness of use cases".

IPS: That's basically coming from a product management and strategy perspective. I'm calling out two things here, both of them about building big data / advanced analytics as a real business capability, rather than a series of one-off experiments.
Shareholder Value
First off, it's critical to assign business outcomes and quantified value to use cases. So for example if you are working on a product affinity analysis, what are the KPIs in your business that will be improved – and what is the range of improvement you should expect to see over a period of time.

Second point I'm making is that a big data capability really pays out when you scale it up. Once you decide to invest in the people, skills and culture, in the right standards and processes, in the platform and tools, then to scale it you need to ensure that your use cases are ambitious enough. The classic cost/volume/profitability logic applies - your costs will stay relatively fixed so it behooves you to ramp up the ambitiousness of your use cases. Don't settle for use cases that everyone else is doing- do those but also target the ones that will provide you competitive advantage.

AR: Q9. In the Big Data vendor landscape, how does SAP differentiate itself from the competition? What do your customers appreciate the most about your Big Data solutions?

IPS: OK to answer this correctly let’s first discuss two key ideas that are absolutely key when it comes to Big Data, but which people are only now starting to appreciate.

One is Scale, and the other is Optionality.

Now that data science is front and center for Boards and CEOs, they want it to quickly scale and grow – but to get a competitive advantage using big data, you need to have both the ability to easily “scale” from small projects to large deployments, as well as the “optionality” of growing into future use cases, connecting to all kinds of data sources in real-time to do a variety of data science work.

For 40 years SAP has been all about providing an end-to-end system: both our customers and our engineers demand no less. The SAP HANA platform provides both scale and optionality for growth as you need it, without having to SAPre-architect and change over all the time. Why? Because it’s built specifically to support big data and advanced analytics – running at scale an In-memory columnar database, with engines for predictive analytics, geospatial and text analytics – we also have something known as Smart Data Access which allows you to connect to virtually any data source. You can have a “Start Anywhere, Go Everywhere” approach because now that ERP is running on SAP HANA, the artificial divide between “transactions” and “analytics” has also started to go away.

So you don’t have to go to multiple vendors for all those things and then to yet others for data storage, data access, information lifecycle management, middleware, security, etc., and then spend time and effort on trying to integrate everything. All that before you even get to model deployment – a key area in which we really stand apart because as world leaders in enterprise mobility we have the technology to let you get the insights from your models into the hands of users, customers and machines.

When you can do all that with one system, you can scale and you can have optionality.

Finally, we have always done things with a deep appreciation and understanding of industry. In fact our entire company is organized by industry, so you have hundreds of people whose entire focus and mission in life, is to look at business challenges and SAP solutions from one industry perspective, so they develop deep expertise and best practices, all of which our customers get not just after they buy our products but as part of the evaluation cycle itself. And we do that for something like 26 or so industries and the public sector.

Between the SAP portfolio, our industry focus, our partners and our startup community, it’s quite likely you will find what you need to innovate, scale and grow.

Gun Germs and Steel bookAR: Q10. On a personal note, are there any good books that you’re reading lately, and would like to recommend? How do you manage work-life balance?

IPS: I’ve recently started re-reading Guns, Germs and Steel by Jared Diamond.

As far as Work-Life balance goes, I try to remind myself as often as possible that we must choose whether we want to “live to work” or “work to live.” As long as I have the privilege of doing what I enjoy, that helps maintain a balance.

Related:

Sign Up