@ThingsExpo Authors: Zakia Bouachraoui, Yeshim Deniz, Liz McMillan, Elizabeth White, Pat Romanski

Related Topics: @DXWorldExpo, @CloudExpo, @ThingsExpo

@DXWorldExpo: Article

Big Data Vision | @CloudExpo #BigData #IoT #M2M #DigitalTransformation

Here are some observations and tips for 'listening and comprehending' more effectively

This is an unusual blog for me. Usually I talk about how organizations can more effectively leverage data and analytics to power their business. However, as I conduct more Big Data Vision Workshops, I have come to realize that a big part of the success of these engagements is the ability to “listen and comprehend.”

Here are some observations and tips for “listening and comprehending” more effectively. I’ve classified this as “facilitation” because I seek to “facilitate” a dialogue with the client where I can learn enough about the client’s business to help them build the right Big Data business strategy.

So this is Schmarzo’s “Keys to Facilitation Success” – the behaviors and characteristics that your team needs to exhibit if you want to do the best job of servicing your clients and building the “right” big data solution:

Be Humble

  • Come to the engagement eager to learn about the client’s business and their challenges.
  • Seek to understand the client’s roles, responsibilities, key business decisions, and the questions that must be answered to support those key business decisions.
  • Remember that the facilitation process is 100% about the client; we are not here to impress the client with our smarts. Don’t try to be the smartest person in the room! Chances are… you aren’t.

Be Respectful

  • Do your homework on the client; show respect for the client by coming prepared.
  • Clients are very proud of what they do and what they’ve accomplished; nurture that pride to get them talking in detail about their responsibilities, pain points, business opportunities and analytic ideas.

Be Curious

  • Listen more and talk less. Period.
  • Encourage everyone to talk – don’t just listen to the loudest person.
  • God gave us 2 ears and 1 mouth for a reason; practice “active listening” (active listening involves paraphrasing to confirm understanding).
  • Don’t be shy about asking clarifying questions; if you do not understand what the client has said (e.g., acronyms) ask to clarify (“Can you please explain?”).
  • Focus on what the client is trying to accomplish, not on what they are doing now. For example, when a client says that they are downloading data into a spreadsheet that is usually a goldmine of analytic opportunities! Don’t focus on what they are doing (i.e., downloading data into a spreadsheet). Instead focus on what they are trying to accomplish (i.e., the analysis they are performing in the spreadsheet).

Be Provocative

  • Be a 5 year old (Why? Why? Why?), but balance the “why” questions with “what” and “how” questions; “why” questions can come across as judgmental while “how” and “what” questions are less threatening while being inquisitive.
    • “What are you trying to accomplish?” versus “Why did you do that?”
  • Sprinkle positive acknowledgments throughout the interview: “That’s a good point.” “Interesting…”
  • Create a “line of questioning” around a particularly relevant topic: “Tell me more.” à “What were the results?” à “How would you do that differently…”

Be Sincere

  • Sincerity shows in your eyes, your posture and your “line of questioning”; be genuinely interested in what the client is trying to accomplish.
  • Be empathic to the nature and challenges of their jobs and responsibilities.
  • Show them you’re listening (look at them, ask questions on what was just said, etc.).

Be Thorough

  • Listen with an ear towards identifying business opportunities and use cases; write them down as you hear them; at the end of the interview repeat them back to the client to verify you heard correctly
  • Take detailed notes; listen especially for things you can write down verbatim as quotes are powerful!

Have Fun!!

  • Smile! You’ve been offered a great opportunity to learn more about your client’s business opportunities and challenges.

The post Keys to Facilitation Success appeared first on InFocus.

More Stories By William Schmarzo

Bill Schmarzo, author of “Big Data: Understanding How Data Powers Big Business” and “Big Data MBA: Driving Business Strategies with Data Science”, is responsible for setting strategy and defining the Big Data service offerings for Hitachi Vantara as CTO, IoT and Analytics.

Previously, as a CTO within Dell EMC’s 2,000+ person consulting organization, he works with organizations to identify where and how to start their big data journeys. He’s written white papers, is an avid blogger and is a frequent speaker on the use of Big Data and data science to power an organization’s key business initiatives. He is a University of San Francisco School of Management (SOM) Executive Fellow where he teaches the “Big Data MBA” course. Bill also just completed a research paper on “Determining The Economic Value of Data”. Onalytica recently ranked Bill as #4 Big Data Influencer worldwide.

Bill has over three decades of experience in data warehousing, BI and analytics. Bill authored the Vision Workshop methodology that links an organization’s strategic business initiatives with their supporting data and analytic requirements. Bill serves on the City of San Jose’s Technology Innovation Board, and on the faculties of The Data Warehouse Institute and Strata.

Previously, Bill was vice president of Analytics at Yahoo where he was responsible for the development of Yahoo’s Advertiser and Website analytics products, including the delivery of “actionable insights” through a holistic user experience. Before that, Bill oversaw the Analytic Applications business unit at Business Objects, including the development, marketing and sales of their industry-defining analytic applications.

Bill holds a Masters Business Administration from University of Iowa and a Bachelor of Science degree in Mathematics, Computer Science and Business Administration from Coe College.

IoT & Smart Cities Stories
The deluge of IoT sensor data collected from connected devices and the powerful AI required to make that data actionable are giving rise to a hybrid ecosystem in which cloud, on-prem and edge processes become interweaved. Attendees will learn how emerging composable infrastructure solutions deliver the adaptive architecture needed to manage this new data reality. Machine learning algorithms can better anticipate data storms and automate resources to support surges, including fully scalable GPU-c...
Machine learning has taken residence at our cities' cores and now we can finally have "smart cities." Cities are a collection of buildings made to provide the structure and safety necessary for people to function, create and survive. Buildings are a pool of ever-changing performance data from large automated systems such as heating and cooling to the people that live and work within them. Through machine learning, buildings can optimize performance, reduce costs, and improve occupant comfort by ...
The explosion of new web/cloud/IoT-based applications and the data they generate are transforming our world right before our eyes. In this rush to adopt these new technologies, organizations are often ignoring fundamental questions concerning who owns the data and failing to ask for permission to conduct invasive surveillance of their customers. Organizations that are not transparent about how their systems gather data telemetry without offering shared data ownership risk product rejection, regu...
René Bostic is the Technical VP of the IBM Cloud Unit in North America. Enjoying her career with IBM during the modern millennial technological era, she is an expert in cloud computing, DevOps and emerging cloud technologies such as Blockchain. Her strengths and core competencies include a proven record of accomplishments in consensus building at all levels to assess, plan, and implement enterprise and cloud computing solutions. René is a member of the Society of Women Engineers (SWE) and a m...
Poor data quality and analytics drive down business value. In fact, Gartner estimated that the average financial impact of poor data quality on organizations is $9.7 million per year. But bad data is much more than a cost center. By eroding trust in information, analytics and the business decisions based on these, it is a serious impediment to digital transformation.
Digital Transformation: Preparing Cloud & IoT Security for the Age of Artificial Intelligence. As automation and artificial intelligence (AI) power solution development and delivery, many businesses need to build backend cloud capabilities. Well-poised organizations, marketing smart devices with AI and BlockChain capabilities prepare to refine compliance and regulatory capabilities in 2018. Volumes of health, financial, technical and privacy data, along with tightening compliance requirements by...
Predicting the future has never been more challenging - not because of the lack of data but because of the flood of ungoverned and risk laden information. Microsoft states that 2.5 exabytes of data are created every day. Expectations and reliance on data are being pushed to the limits, as demands around hybrid options continue to grow.
Digital Transformation and Disruption, Amazon Style - What You Can Learn. Chris Kocher is a co-founder of Grey Heron, a management and strategic marketing consulting firm. He has 25+ years in both strategic and hands-on operating experience helping executives and investors build revenues and shareholder value. He has consulted with over 130 companies on innovating with new business models, product strategies and monetization. Chris has held management positions at HP and Symantec in addition to ...
Enterprises have taken advantage of IoT to achieve important revenue and cost advantages. What is less apparent is how incumbent enterprises operating at scale have, following success with IoT, built analytic, operations management and software development capabilities - ranging from autonomous vehicles to manageable robotics installations. They have embraced these capabilities as if they were Silicon Valley startups.
As IoT continues to increase momentum, so does the associated risk. Secure Device Lifecycle Management (DLM) is ranked as one of the most important technology areas of IoT. Driving this trend is the realization that secure support for IoT devices provides companies the ability to deliver high-quality, reliable, secure offerings faster, create new revenue streams, and reduce support costs, all while building a competitive advantage in their markets. In this session, we will use customer use cases...