Jack Phillips from IIA interviewed by VL for 7 questions series data and supply chain data integration

7 Questions Data and Supply Chain Data Integration: Jack Phillips

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 The 7 Questions Interview Series: Data and Supply Chain Data Integration

The 7 Questions Interview Series: Data and Supply Chain Data Integration “The 7 Question Series” is an investigative content series where we seek out key leaders in a specific industry and/or subject matter expertise area and ask them 7 key questions that “enquiring minds want to know”. There is a twist however to these questions. We provide the person being interviewed with a hypothesis for each question. This helps to frame and set context for their answer.

Data and Supply Chain Data Integration Series Objectives:

Data and Supply Chain Data Integration Series Objectives: The objective of this series is to establish direct connections with data experts across the globe and ask them the same set of 7 questions regarding data and data integration in the business. We want to derive insights from their direct experiences and expertise that will help companies, both B2B and B2C at all stages of their evolution. We are also curious to see if their answers are similar or different. These interviews will be featured on this website as a series.

The Interview with Jack Phillips, CEO & Co-Founder at International Institute for Analytics (IIA)

About Jack:

Jack_Phillips_Headshot

Jack Phillips is a noted advisor and writer on the impact that business analytics and big data have on enterprises. Mr. Phillips founded the International Institute for Analytics (IIA) with Tom Davenport, and currently serves as its CEO. Mr. Phillips edited the 2012 book Enterprise Analytics: Optimize Performance, Process and Decisions Through Big Data.

In his work at IIA, the leading independent research and advisory firm that works with with companies to build and support competitive analytics programs, Mr. Phillips focuses on how the adoption of data and analytics by certain firms leads to competitive differentiation and higher performance. Mr. Phillips speaks frequently on cultural changes, organizational models, talent acquisition and the requirements of new leaders in a data-driven world.

Mr. Phillips is a graduate of the Harvard Business School and Williams College, and lives with his wife and three children in Portland, Oregon.

 

 

The Interview:

Robin Smith: Has the term Big Data been over hyped? There is a sense of “Big Data” fatigue, backlash even, that seems to be becoming more prevalent. Is Big Data relevant?

Jack: Certainly, we at the International Institute for Analytics have been saying for a couple of years now that the term “big data” is a bit overhyped. While it does carry meaning as a descriptive term, the fatigue that you’re sensing primarily comes from the failure for companies to match their hopes and expectations with actual business outcomes generated by investing in big data.

No company is going to be successful working with big data if they aren’t also competent at working with traditional “small data.”Analytics, even on small data sets, is something that major organizations struggle to embed in everyday processes to drive real business value. We sense that over time companies are starting to realize that big data, structured or not, doesn’t always come from the internet, isn’t that much different from other data types, and should be fully integrated with other sources of internal data.

We developed our Analytics 3.0 framework to explain the potential outcomes when businesses can combine big data and traditional analytics. Businesses that can do that, and embed analytics directly into decision and operational processes, taking advantage of machine-learning and other technologies to generate insights in seconds rather weeks or months will have a real competitive advantage. So the promise still exists, it’s a reality in some cases, but for most businesses the hard work is still to come.

Robin Smith: Do you really need data scientists as part of your big data strategy? What are the characteristics required of a data scientist? Does this have implications for our educational systems?

Jack: When developing a big data strategy, the most important consideration has to be the economic impact on the business. Above all else, the strategy has to align with corporate goals to deliver tangible business impact. The stakes are too high for companies not to embrace this new way of data-driven decision making.

Gone are the days of the data scientist working alone in their “data cave” delivering analysis in a black box.  To the extent that data scientists can align with business goals to make that impact, they can be tremendous resources for an organization, by virtue of their ability to apply statistical and mathematical techniques to large data sets.  The implication for our educational institutions and for the business world is that the education of a data scientist cannot be limited to math, stats and computer science. Data scientists become far more valuable when they come with a business perspective, and are embedded within functional lines of business, focused on developing and implementing solutions to real business problems.

In the 5+ years since I co-founded IIA with Tom Davenport, with all the analytics research we generate and the clients we advise, you’d be amazed how often companies get this wrong. Organizations focus on quick fixes like technology, or data scientists, and forget about culture, or picking the right problems to solve with analytics, or they fail to get corporate leadership to support the work they are doing. Data scientists and analysts are a big piece of the puzzle, to be sure, but these other factors are just as critical with any analytics or big data strategy.

Robin Smith: Is the relational database, the foundation of the data warehouse in the small data world, still relevant in a big data age?

Jack: Despite a media-driven idea that the “low cost” Hadoop can replace the “high cost” RDMS (Oracle, Teradata, etc.), this couldn’t be further from the truth.  The future, high-performance analytics technology stack will consist of both data storage technologies, primarily divided between non-production, experimentation-oriented environments (Hadoop) and production environments (traditional RDBMS).  The traditional relational database is absolutely necessary in the future environment.  The data strategies that will emerge from these two environments will reflect the usage patterns described.  That is, firms who are implementing Hadoop are developing data governance and management practices that fit the Hadoop environment, but would not be strong enough for the production, RDBMS environment.

Robin Smith: Given the reputation and organizational risks involved in poorly governed data (privacy, breach, quality), should data governance be a corporate governance imperative? Where should ownership of this risk reside, should companies have Chief Data Officers?

Jack: Data governance certainly should be a corporate priority, but it rarely is inside enterprises.  True understanding of, and appreciation for, the risks associated with data assets is still low at a corporate level. Most end-users understand the risk in principal, but data governance exists in division units in most organizations rather than corporate-wide.

Without question the risks (privacy, security, quality, accuracy) associated with data are increasing across all sectors.

Robin Smith: Is big data only for big companies with deep pockets?

Jack: Quite frankly, the barriers to utilizing big data are as low as they have ever been, historically. The cost to store and manage data, on premises or in the cloud, has never been cheaper. Open-source technologies like Hadoop and R have allowed companies of all sizes to install, experiment and start working with big data to drive significant business decisions. We know this to be true with Fortune 500 companies, as it is with the myriad [of] lean startups that were born digital, collect data with purpose, and think of analytics as just something that today’s businesses need to do, the same way they need to have finance, sales and HR.

Robin Smith: How has data changed the way business should look at their systems?

Jack: When acquiring new systems and technologies, firms are certainly evaluating systems through the lens of all things data….acquisition, quality, cleaning, etc.  Firms with legacy systems are struggling since legacy systems aren’t able to handle the data requirements being demanded by firms today.

Robin Smith: Data ownership and value has become the latest discussion point in the data hype cycle. Has the accounting and legal paradigm changed enough for data to be defined as an asset on the balance sheet and has ownership been clearly delineated from a legal perspective?

Jack: We fully expect that companies will soon in fact report their data as an asset on the balance sheet. We’re also expecting that companies will begin to report out on their analytics maturity to shareholders, the way they do for sustainability. The key challenge here that have implications for lawyers and accountants is how can you put a number on the value of data that is accurate and defensible, not only to regulators, but also to shareholders. One way to overcome the challenge is starting to emerge, as companies are increasingly starting to buy new data, and sell some of the data they collect. Our expectation is this emerging data monetization market will not only generate new revenue streams for businesses that are conscientious about collecting data, but also help accounting teams better understand the value of the data they own.

Jack’s Social Outposts Twitter | LinkedIn | Website | Blog

About IIA

Founded in 2010 by CEO Jack Phillips and Research Director Thomas H. Davenport, the International Institute for Analytics is an independent research firm that works with organizations to build strong and competitive analytics programs.

IIA offers unbiased advice in an industry dominated by hardware and software vendors, consultants and system integrators. With a vast network of analytics experts, academics and leaders at successful companies, we guide our clients as they build and grow successful analytics programs.

Since its inception, IIA has worked with more than 200 organizations, sharing the keys to analytics maturity so that our clients gain an edge in an economy increasingly driven by data. Through our in-depth research library, moderated phone calls, webinars and events, our clients get the guidance and expertise needed to compete on analytics and win.

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