Part 2 of the three-part interview series, “Unlocking Intelligent Innovation,” with Maggie Buggie, senior vice president and global head of SAP Leonardo Services at SAP
The spark of an idea and inspiration is an exciting time during the innovation process. And to fan the flames, businesses need to create and validate a working model, better known as a prototype.
But there’s a catch: Prototyping is more than just checking whether the innovation is feasible, scalable, desirable, and viable. The real work is knowing how to deliver long-term, meaningful outcomes to the organization and understanding how the innovation changes human behavior, process, technology, and regulatory compliance.
In Part 1 of this series, Maggie Buggie, senior vice president and global head of SAP Leonardo Services at SAP, alluded that some business innovations stay trapped in the prototype phase due to a lack of context. “Without context, there’s no value in innovation whatsoever. Having technology wrapped up in a shiny new prototype is not the end goal,” she said. “Customers can save an awful lot of time, money, human emotion, and frustration if they remember this principle.”
In this blog, we continue this conversation – covering topics from the proof-of-concept trap to a prediction on the future of innovation.
Dominik: Maggie, what is the proof-of-concept trap and how dangerous is it to the success of innovation?
Maggie: The proof-of-concept trap refers to that moment when a company develops beautiful ideas, builds shiny prototypes to evaluate them, and fires up the company on their value – only for the sledgehammer of reality to pummel progress. The company can’t deploy the innovation because it does not have the right technology, business process, or culture in place to support it.
Unfortunately, this is what happens when a business does not look at the full picture when considering how innovation and intelligent technologies can make a difference to the company. After spending countless hours, significant capital, and tremendous brainpower on the innovation, the business finds out that it needs to implement a technology stack or its components to build a supporting foundation. And worse, it’s possible that the required technology is more mature than the existing IT architecture.
Although this is a frustrating event for everyone involved, it’s also one of those crossroads where providers, such as SAP, shine. From the beginning, businesses need to scale their view through a more pragmatic lens. Businesses should discuss with their partners what’s possible for their innovation and help ensure that the effort delivers what matters most – real, meaningful outcomes over time.
Dominik: How does scaling innovation, as you described, help businesses avoid that trap?
Maggie: Scaling innovation from the very start helps flush out enablers as well as blockers of the process and the final deliverable. If a business creates a prototype and wants to roll it out across 7, 15, or 30 sites, deployment can become quite complicated if those obstacles are in the way.
Take, for example, how an innovation changes how people work. Suppose a new process calls on employees to use a more advanced version of analytics. This new requirement can significantly impact how the workforce adopts the innovation, leverages it to its fullest potential, changes organizational roles, and engages with the rest of the business. Think about it: Should a business be comfortable with allowing certain workers to self-direct action based on real-time data flows – especially when they were not allowed historically to make those decisions by themselves initially?
It is also critical to comprehend how the new innovation capability changes how business value is conceived and measured. Imagine if a business is looking at using machine learning and artificial intelligence to run digital marketing programs. The meaning behind key performance indicators, such as customer lifetime value, can shift significantly because customer relationships will change and new opportunities for monetization will emerge.
Both of these implications – and many more – can considerably influence the success of the initiative. It’s always best to know early on when a planned innovation is not working out as desired to save the business from the unnecessary cost and wasted energy on an innovation that delivers nothing.
Dominik: Do you foresee the prototype creation and validation phases of innovation changing as technology becomes more powerful and business become more digitally mature?
Maggie: I would hope that prototype creation and validation will improve. However, my long experience in this space tells me that the phases will only become more complex. We’re going to see an even higher demand for people who have real-world experience in the new world as well as the old world.
As this market matures, we will start to reconsider what a real-time, intelligent enterprise looks like from an organizational design point of view. Organizations will need to reposition themselves to respond to external events faster. There will be substantial pressure on the speed of decision-making and workforce performance. Plus, the ability to comply with industry and government regulations – including the General Data Protection Regulation (GDPR) – will become of greater importance when evaluating innovations.
And for prototyping itself, I hope that it will become more formalized and focused. Prototyping is designed to only reduce deployment time and shorten the gaps between idea, conception, modeling, live deployment, and financial realization. The phase would be used as a stepping stone on the route towards the ultimate course of action and outcome.
Will these developments put an end to the proof-of-concept trap? I guess will find out the answer in due time. But a greater understanding of the role of prototyping will definitely increase the chance of avoiding it.
Balance deep consumer, technology, and business knowledge to generate novel ideas and progress them to scaled deployments. Find out how your business can apply innovations – such as machine learning, artificial intelligence, advanced analytics, the Internet of Things – with SAP Leonardo Services.
About Maggie Buggie
Maggie leads SAP’s digital innovation services business globally, helping companies create and maximize business value through the use of intelligent technologies such as IoT, machine learning, AI, blockchain and advanced data analytics. She has significant experience building fast-growth digital businesses and previously led Digital Sales globally at Capgemini and Global Cloud Sales & Consulting for Fujitsu.
Maggie holds both a Master of Letters and a BBS Lang in Business and French from Trinity College, Dublin. She also holds a degree from the Grande École de Commerce de Rouen, France.