Adaptive Live 2019: All Systems Go

Source: Adaptive Insights

Last week, I spent several days at Adaptive Live 2019 in Las Vegas. Overall, I was very impressed with Adaptive Insights evolution and focus, post-acquisition, as it continues to support existing customers while quickly aligning to Workday’s broader technology and go-to-market strategy.

Even though Adaptive launched its’ Sales Planning and Workforce Planning offerings this past year, not surprisingly ninety percent of the 1,600+ conference attendees were there to celebrate the firm’s well-respected Financial Planning heritage and tools.

The event had a number of useful customer panels, and guest-speaker keynotes. For me, however, the highlight of the event was spending time with the leadership team in a series of small group analyst briefings, as well as hearing what’s coming next.

For some time now, I’ve been very impressed with the team that Tom Bogan assembled after becoming CEO in early 2015. This includes, but is not limited to, Bhaskar Himatsingka, Adaptive’s Chief Product Officer, who has done a great job laying the groundwork over the past couple of years for what could potentially be some game changing analytic offerings.

In July 2018, just prior to its aborted IPO, Adaptive announced that it had fundamentally rearchitected its planning, reporting and analytics engine, leveraging what it called “Elastic Hypercube Technology.” Essentially, this new approach provides for unlimited dimensions, dimension values and versions – and does so in a manner that is highly efficient (especially in sparse data scenarios).

A year later, Bhaskar shared that virtually all customers are now on this platform – with many leveraging the new hypercubes at significant scale. While the new platform provides a significant improvement in performance, it also sets the stage for Adaptive to layer in a range of artificial intelligence (AI) and advanced machine learning (ML) technologies, both of which will likely help transform the Finance function over the next decade.

AI and ML Initiatives

Bhaskar highlighted several key initiatives in what Adaptive is calling its “Intelligent Planning Roadmap.” In the short-run, the focus appears to be around automating often mundane processes – such as its soon to be released “Anomaly Detection” offering. Mid-term, the firm emphasized that it will also focus on more strategic initiatives such as the development of “Augmented Analytics” – which, I would presume, could be a basket of capabilities that harnesses data and predictive analytics, supporting and enhancing, rather than replacing, work activity.

It will be interesting to see how the new Data Access Layer that Workday has been developing will not only connect all three of its engines (Workday’s core in-memory database, Prism and the Adaptive hypercube) – but also support its broader ML plans (see Workday Innovation Summit: Key Takeaways).

Based on a series of one-on-one side discussions with nearly a dozen attendees (both existing customers and some prospects), it appears that Adaptive is poised for continued growth – not only organically within its own suite of offerings, but some cross-sell into the broader HCM and Financial Management offerings of its parent Workday.

Emerging Skills Crisis in Finance Real

I walked away from the event even more convinced that Finance is in for a significant restructuring – and we are not talking decades away. While yesteryear’s layering of new, more strategic roles and responsibilities will no doubt continue to have a transformative impact – AI-driven process automation and the emergence of ML-led workflow augmentations will demand a new, more analytics-focused workforce. The coming skills crisis in Finance is real.


ML and AI Signposts

Source; McNee Associates, 2018, N=265

I’ve been attending a number of industry events recently that squarely position machine learning (ML) and artificial intelligence on the forefront of change. Last year, McNee Associates conducted original research with 265 senior business and IT executives in the US, Europe and Asia, to get their sense of the shifts that are occurring.

As the graphic highlights, the use of AI and ML is projected to grow rapidly and broadly over the next couple of years. Our research indicates that 52 percent of executives believe that that their firms will be “gaining scale” or “fully scaled” in their use of AI and ML by 2021, up from only 13 percent last year. Having conducted similar research on next-gen technologies over the years, the slope of change here is significant.

Across the entire spectrum of cloud infrastructure and apps — from vendors such as SAP, Service Now, AWS, Workday, IBM and others — what is clear is that ML and AI are no longer futuristic technologies, but in the here and now. The range and ways that AI and ML are being imbedded into solutions is vast, and often times largely invisible to the ultimate end-user.

Additional insights from the research:

  • 60 percent of execs believe that AI and ML will fundamentally change their industries.
  • Almost 34 percent of execs believe that AI and ML will result in significant job losses. Interestingly, US-based IT and business leaders are more optimistic than their colleagues in Europe and Asia (20 vs. 46 percent). This may suggest that they believe these technologies will play more of a supportive role, augmenting existing skills, or that significant retraining can occur for those displaced vs. wholesale layoffs.
  • RPA led our list of AI technologies in use, followed by Chat Bots, Expert (knowledge-based) Systems, Machine Learning, and Virtual Assistants, among others.
  • Predictive Analytics led the list of top technologies / trends / capabilities that will have the biggest business impact through 2021, followed by Cyber Security and Digitization of Products and Services.
  • As expected (based on previous research conducted in this space), Company Culture and Organizational Willingness to Change topped the list of obstacles / challenges IT organization’s face to successfully navigate the emerging technology-enabled business landscape.


Workday Innovation Summit: Key Takeaways

A little over a week ago, I traveled west to participate in Workday’s annual industry analyst event – now appropriately rebranded the Workday Innovation Summit. As has been the tradition now for several years, the event was held at the beautiful Cavallo Point Lodge, in Sausalito, CA, just below the Golden Gate Bridge.

Source: Workday

While much of the day was spent focusing on Workday’s continued innovation across its HCM and Finance application suites, growing analytics and Cloud Platform capabilities, and AWS support – the theme of extracting greater and greater value for customers, and augmenting executive decision making through machine learning was central to the day. To this end, Aneel Bhusri, Workday’s CEO helped kick-off and frame the day by emphasizing that “machine learning is the fundamental technology of the future.

The good news is that Workday already has a powerful and unified platform that supports many of the key threads of 21st century architecture. Importantly, I came away with a sense that Workday is taking a very realistic approach to their machine learning (ML) investments – focusing on augmenting the user experience, rather than as a replacement – as it builds out a portfolio of algorithm’s that can be applied to a range of business use cases. I’ve just loved the Phil Mickelson “Business Caddy” ads Workday has been running for the past 6-9 months that emphasize, in a non-technical way, machine learning as supportive to executive decision making.

Fundamental to the successful execution of this strategy has been a focus on extracting more and more value from the data that Workday already manages, as well as helping it increasingly become a hub that leverages a broad range of enterprise and external data.

I really liked what I saw in regard to the emergence of a single data access layer and analytics engine (see chart) that will help coordinate all of the data (and machine learning services) across its now extended family of products. While the initial use-case will no doubt bring Adaptive Insights into the “Power of One,” the longer-term implications of Workday’s vision for a single reporting architecture could help the company more quickly integrate potential future (functional) acquisitions as well.

I look forward to learning more about this initiative at the Adaptive Insights event in Las Vegas later this month. In closing, I’d like to share how impressed I always am by how well-run this event is, and how open and frank the entire Workday team is in both sharing and receiving feedback about its future plans. This year was no exception. Well done.


Authored by on December 15, 2019 at http://mcneeassociates.com/2019/05/


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