Notes From Alteryx Event

I just finished watching the Alteryx event that was live streamed today titled “ACCELERATING DIGITAL TRANSFORMATION IN COVID TIMES”. The presentation was about 50 minutes in length and you can watch it here after you register:…

High Level Summary - This event was an evangelizing event- Alteryx wants companies to buy into Analytic Process Automation - COVID-19 is a perfect opportunity to retrain those who need a new skill set.

A. Organizations are trying to learn how to bring more data analytics into their organizations for a variety of reasons ranging from increasing revenue/productivity to creating more meaningful jobs for employees. This requires organizations and employees to change and grow.

B. Some organizations fear change and employees are wary of AI & machine learning if they think their jobs may become replaced by automation.

C. Analytic Process Automation (APA) is a new category of software to help organizations take tedious and complex tasks and automate them. The goal is to help companies transform their culture to embrace data analytics.

D. The COVID-19 pandemic has cause large numbers of employees to be displaced and have the time to learn new skills. Alteryx is offering a free opportunity for folks to learn data analytics through the Alteryx platform giving them the opportunity to reenter the workforce with a new skill set.

Here are my notes:

  1. There were five participants. The host was co-founder of Alteryx and Chief Customer Office Libby Duane Adams. The panel consisted of Chandana Copal a Research Director at IDC, Suneet Dua Chief Product Officer, PwC U.S., Rod Bates V.P.Decision Science and Data Strategy Coca-Cola N.N. and Dean Stoecker CEO of Alteryx.

  2. Point solutions are not very useful as they effect some data, some people, some of the time, and go after low hanging fruit. (Libby Duane Adams)

  3. Typically the IT department is where an intro to data analytics begins. Companies really need to involve its entire workforce if it wants to reinvent the culture around using data.The hardest part is getting the people to buy into the process. (Libby Duane Adams)

  4. Typical classroom training is sub-optimal as you have folks from many different levels of skill and they all learn differently. Working at each individual’s own pace gives much better outcomes. (Libby Duane Adams)

  5. Data analytics does not work in “silos” within an organization, you must be able to do it at scale. IDC did a survey and found that out of 150 CXO’s 87% said that enterprise intelligence is a top priority over the next five years. (Chandana Copal)

  6. PwC did a survey of CEOs and 74% said they are concerned about their people and they have an up scaling agenda. To really improve a company must do so at scale and create a culture of innovation. (Suneet Dua)

  7. Coca-cola believes it could gain a competitive advantage of it takes advantage of all the data it has. Workers want to understand how their jobs may be impacted and Alteryx provides a tool set to help people see they can learn new skills and be effective at data analytics. (Rod Bates).

  8. Dean talked about how only 3% of the world’s data is being effectively utilized and $10T to $15 T is locked up in data. He talked about how the workforce must be up scaled and he believes we are at a tipping point with regard to democratizing data analytics.

  9. The Alteryx platform provides employees of various skill levels to analyze data without writing code or using a data lake. Coca-Cola needs this as it allows a wide range of employees to become knowledgeable. (Rod Bates)

  10. Dean said democratizing data provides better insights and better outcomes. If you want to find a needle in a haystack you have to be able to first see the entire haystack.

  11. You have to break it down so people understand the framework of automation. decide whether a machine or human can do which part of the process better - buzzwords like AI and machine learning can be scary for workers. An example - Machines can read medical images of a patient and compare with millions in a database better than a human. A human is much better at prescribing a therapy & dealing with the patient holistically.(Chandana Copal)

  12. Coca-Cola is using analytics in areas such as advertising/marketing, supply chain, and financials - it effects every part of the business. (Rod Bates)

  13. On the human side of digital transformation it must be done at scale. PwC does it side by side as opposed to tops down. Digital citizens working with business units. Build innovation into the organization.

PwC has come up with a new product/solution called “Pro Edge”. Training must be structured to the individual creating an infinite learner. People can grow by creating automation and be celebrated at heroes within an organization. (Suneet Dua)

  1. Dean said the approach must be more business to consumer than business to business. People must realize that a human centered platform will help them move forward. Normal folks can be retrained in this area.

  2. Customer retention and employee satisfaction are two goals that are not defined by money yet are real potential outcomes of digital transformation. (Chandana Copal)

  3. Three areas of focus in the eyes of IDC for data analytics are increased productivity gains, new revenue streams, and the most important a change in culture.(Suneet Dua)

  4. Dean encouraged folks to simply get started - stock to a center lane opportunity and go for it. Do not work on an edge or corner case at the outset.

  5. focus on where the organization wants to go. (Rod Bates)

  6. Break down processes into tasks and see where you can apply analytics to get started. (Chandana Copal)

  7. The process used by IDC is to create three buckets to get going & make it fun. Start with an assessment process, then create micro-learning experiences leading to micro-credentials, celebrate employees achieving goals, and finally share the created asset across the business.

Dean closed it out by saying analytics is a social experience and companies need a high degree of sharing of workflows.

Frank - long AYX, see profile for all holdings