Whenever I find myself needing some reflection, or the need to refocus on the bigger picture, I think of one of my favorite poems: “Ithaca.” Not the island home that was the goal of Odysseus’s years of wandering, but the journey itself.
In Homer’s original epic poem, many people seem to take it that Odysseus always longs for home. And it is understandable. Few of us enjoy a long journey when it is full of perils. We read the book as Odysseus continues to look to his home in Ithaca for peace, security, and love. Most people read it and focus on the destination. Yet when I read Cavafy’s “Ithaca,” the reverse seems true. It’s the journey that’s valued—the destination is dismissed as of no importance.
What I like so much from Cavafy’s “Ithaca” is his point of view that it’s the journey that must be fully enjoyed at every moment, using all the resources of senses and intellect, because the goal itself is likely to be disappointing without the realization of the growth that the journey brings. Odysseus was fortunate to recognize the journey was the reward, not the destination.
Having been part of IBM’s formative years in AI with Watson—from winning “Jeopardy!” to figuring out how to turn a cute quiz show-dominating machine into a serious business contender and AI platform—SAP Leonardo feels for me the natural next step in my journey.
A career and journey that started by applying data points from observed consumer behavior to statistics and Markov models. A journey that allowed me to live and work in nine countries across three continents.
A journey in which a common theme emerged: data monetization—using process and client interaction data to drive insight and actions. To create business value. To give rise to a new economy with data as the driver for growth. Well, not exactly data as driver for growth, but more the “thing” that companies do with data as a driver for growth. And innovation. And sometimes even driving disruption. Yet always with growth and business value at the core of a strategy.
Transforming enterprises into data-driven organizations—fact-based, forward-looking, exception-oriented, value- and growth-creating organizations—has been the common theme of my track record. With clients, employers, partners, researchers, data scientists, and in product development, service creation, and offering management.
For those who have met me, you know, I love to work with clients and to provide clients with solutions to solve their business problems. And I wanted to create and drive something more for my clients. Today, most artificial intelligence offerings are machine learning code, API services, and a few solid AI platforms, mostly for developers. Few of us get great satisfaction out of an IKEA assembly experience. In my perception, the same applies for enterprises.
What the market needs is an AI solution. A toolkit. A sort of iTunes, where it doesn’t matter whether the songs are provided by Apple, ripped from a CD or DRM-free (bought from another provider) or my own recordings. iTunes acts as the combined ecosystem that allows me to manage my songs and to orchestrate usage, like workflows, playlists, favorites, or ringtones.
For me, nothing is as fulfilling as seeing your clients having sustainable success with your advice, your product, or your solution. After all, the only sustainable source of profit and growth are happy profitable clients (that is, unless you are the IRS—they play in another league). Yet, having worked 25+ years through the natural evolution from business intelligence to advanced analytics, Big Data, and AI, I felt the need for the next destination in my journey.
Enter SAP Leonardo. Imagine one capability of orchestrated AI services that do one thing, for instance, reconciliation. Now imagine a toolkit that allows you to mix and match that capability and infuse it within your solution. Like reconciliation for invoices (reduce 60% manual reconciliation to 5%), or travel expense/claim reconciliation, salary compensation reconciliation for an employee who had multiple roles over one year, or contract terms alignment.
All I wanted for the next step in my journey is to set the strategy, create, and play with such a solution toolkit. Create value and offerings that didn’t exist yesterday, where the robots do the heavy lifting and the humans do the thinking. To boldly go into markets where no AI has gone before.
So, as I see it, SAP Leonardo is not a platform, nor a program, nor a single entity—SAP Leonardo is a digital business system, a set of tools to build new style applications. AI-infused capabilities that both SAP developers as well as SAP clients or SAP business partners can use to extend their specific SAP solution and create a customized addition based on the client’s knowledge.
Imagine a tools set that acts as framework. Handles life cycle management—but for knowledge. Trained knowledge—it’s like a teaching physician checking in each week on a resident, training them on the secret sauce of the hospital, and correcting them when their assumptions and knowledge needs changing.
Now compare that to traditional, rule-based software. When the rule changes, the software needs to be changed. But with an AI toolkit, we’ll just promote or demote the training data, like a merchandiser telling a new hire, “Yeah, this case is different from this month forward given the new regulation, so our new-hire training doesn’t apply anymore.” With software, we need to change the rules. Yet, with humans, we don’t replace the new hire with another one just because the regulation changed. We just retrain them. And that’s where an AI toolkit comes in. It (supervised) retrains the machine learning, yet it doesn’t change the application.
That’s what SAP Leonardo will do for clients—that’s how it helps drive their digital innovation. That’s the journey that I am taking with SAP Leonardo.
Thank you for reading this blog. May your journeys be marvelous.