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 James Rodmell, CTO / Partner at LEMON Mobile LLC.
James is a futurist; passionate about technology; experienced, connected and creative. James sees how things fit together and is able to articulate options and solutions to complex problems. He has developed the concepts (including site maps, wireframes and architecture diagrams) for multiple enterprise web, mobile and data projects, and has over 15+ years’ experience implementing and managing these types of projects.
As the CTO of LEMON Mobile LLC., James has a deep understanding and empathy for all positions within a company; from administrative to driving the business and leading the vision and strategy. He has hands-on experience in the trenches and in the boardroom.
James excels under pressure, understands and can communicate with developers in many code languages and is considered a pioneer in the mobile and data space by many highly recognizable peers and colleagues.
Robin Smith: Has the term Big Data been over hyped? There a sense of “Big Data” fatigue, backlash even, that seems to be becoming more prevalent. Is Big Data relevant?
James: I believe a major problem with big data companies has been their approach. Their champions rushed to collect and crunch data without asking “why are we doing this?” and once done, “what did it tell us” AND once told, “how can we act on it and adjust to improve what we are doing?” This approach is changing rapidly as the tools for visualization and analysis catch up. I believe that big data analysis and questions should be originating from the marketing, operations and sales teams, business development, customer service managers and not from the data scientists per say. It is the job of the data scientists to educate the company on what is possible (in plain language) but the concepts and goals should be created and driven from elsewhere in the company.
More and more we do see that , these “data scientists” are actually working closer with marketing and other key lines of business. In fact, an emerging role is that of the “Chief Digital Officer”. This executive sits alongside a CMO, CTO and CIO, all reporting into a single office. This CDO (even more than the CTO) is building the teams to coordinate the different objectives related to big data gathering, analysis and reporting.
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?
James: A data scientist is an important member of a big data strategy team and I foresee the demand for this role increasing. This means that our schools will need to offer courses and curriculums better suited to support this emerging requirement in the workforce. For example, today, the people I am seeing out there in this role usually have a good math background coupled with database design. Hadoop/Mongo combined with new data ripping algorithms and software (like Splunk) are making the job far easier and accessible to non-data scientists. That said, in a recent article, McKinsey Global Institute reported that by 2018 the United States will experience a shortage of 190,000 skilled data scientists, and 1.5 million managers and analysts capable of analysing and interpreting big data and garnering insights from it. This potential shortage is rather alarming but the good news is that the tools are getting so much better that I expect non-data scientists who apply some logic will be able to uncover good insights.
Robin Smith: Is the relational database, the foundation of the data warehouse in the small data world, still relevant in a big data age?
But that said, our strategy developed over time. We went in with one idea and it evolved and changed direction due to what the data told us and what we realized we could do with it. As technology changed and evolved, new data sets emerged and were generated, which in turn changed our strategy. I guess one must assume that their big data strategy will adapt and change, even in its infancy and that it must be flexible enough to evolve. An example of this was our realization we could calculate things like dwell time from enter and exit events with geo-fences. This discovery – or realization – led to new strategies – which in turn created new business models.
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?
James: Any personally identifiable data (PII) must be protected with the senior leadership team being accountable for proper oversight and governance. In many businesses, this data and its use in predictive analysis, is one of the company’s greatest assets. Its protection and safe-keeping can literally mean the success or failure of an entire company, not just a division or department. This is why we’re seeing new strategic executive roles like the Chief Digital Officer and the increased importance and stature of the CIO. These leaders are taking on more responsibility to manage, store and protect data on behalf of the executive team and the Board.
Robin Smith: Is big data only for big companies with deep pockets?
James: Not anymore and nor should it be. With platforms like Tableau, GNIP, social analytic sites, Amazon S3 and a little planning, even small to medium businesses can glean amazing insights into customer habits, inventory and predicting sales peaks and troughs.
Robin Smith: How has data changed the way business should look at their systems?
James: When Excel came out, there were a few users out there who understood the power of this accounting tool. Over the years it got better and better and an Excel master is truly a data expert now. Companies will need to go through the same progression as with the early desktop tools. Much of this will be about “how” to collect new data which corroborates current findings or sheds light on existing but under-used data sets. Companies will need to uncover what data they need – and this is more of the marketer led thinking, as opposed to the data scientist.
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?
James: The value of data is inextricably linked to the price people will pay for the data and the insight it provides. Just holding on to vast amounts of data for the sake of it is not a smart plan and the costs (though continuously dropping) will quickly outweigh the benefits. That said, with customer data and machine data collected from sensing devices (WiFi access points and mobile phones for example), and with the rise of The Internet of Things there will be the ability over time to see if small changes to way-finding paths in a shopping mall change shopping habits based on how building management configures the entrance and the path people take. With historical aggregate data of the retail shoppers journey, building management can make the shopping experience better for the consumer and the retailer.
About Lemon Mobile LLC.
LEMON is a global hybrid mobile marketing platform providing geo, proximity and micro-location based mapping, triggering and messaging with advanced data analytics for contextual, relevant and interactive engagement. LEMON delivers highly accurate, location-based in-app push messaging, turnkey creative and campaign management, geo-fencing and innovative data analysis so you can customize your marketing strategy around your most important asset – your customers.
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