Today: As is tradition, AWS released all the news that won't make the re:Invent keynote ahead of time, the Allen Institute for AI introduces a powerful and truly open-source AI model, and the quote of the week.
This era of enterprise software is either the dawn of a new era of corporate productivity or the most hyped money pit since the metaverse. ServiceNow's Amit Zavery talks about the impact of generative AI, how SaaS companies should think about AI models, and his decision to leave Google Cloud.
How Cushman & Wakefield got control of application sprawl
A convoluted series of mergers, acquisitions, and divestitures had left Cushman & Wakefield with "hundreds" of separate enterprise-resource planning applications. It wanted a flexible but standardized base to get everyone on the same page.
The commercial real estate market has been through a roller-coaster ride of ups and downs since Cushman & Wakefield emerged from a series of private-equity deals as a public company in 2018. While the century-old company couldn't have foreseen the rapid changes in this market caused by the pandemic, it did foresee the need to build a new digital platform on which to ride the rails.
Right after that IPO, the company decided to focus on partnering with SaaS vendors rather than maintaining a swath of applications when adopting its cloud strategy, said Sal Companieh, chief digital and information officer. Several different real-estate companies came together through its private equity partners to form the pre-IPO organization, and it wanted a flexible but standardized base to get everyone on the same page.
"We strategically created an environment where we have afforded ourselves the privilege of focus on our data," said Companieh, who has been with Cushman & Wakefield since 2015 when it merged with competitor DTZ. "The reason we went down that path is because we knew that with configurable technologies … it afforded us the ability to really concentrate on bringing data to life."
A convoluted series of mergers, acquisitions, and divestitures had left Cushman & Wakefield with "hundreds" of separate enterprise-resource planning applications, Companieh said. It slashed that down to two, and around the same time cut several human resources apps down to just one, standardizing on Workday.
"We've gone from hundreds of dispersed local platforms with unique data models to the global platform, global data model," Companieh said. "The hypothesis was if we created a financial and HCM (human-capital management) backbone from the core, then we could tether into it with each of the product lines."
That second shift started to take place when Companieh became CDIO across the entire company almost two years ago. Standardizing on core SaaS applications made it easier to manage Cushman & Wakefield's data, but it's a big company with different lines of business; property brokers prioritize different datasets than asset managers, for example.
"We had platform owners, we had technology owners, but we didn't have them tethered for the experience of a product," she said. Now there are "technologists waking up to optimize the data and the digital workflow for every single one of our products that we sell to our clients."
AI is kind of like home decor; what works for one company will not work for another.
Cushman & Wakefield was ahead of the curve when it came to paring down its enterprise software assets to work closely with a smaller number of vendors. The early days of enterprise SaaS were characterized by the "best of breed" mentality, in which department-level managers were more or less free to pick the tools they thought were best for their needs, and emerging companies sold business software by emphasizing their laser focus on a particular feature.
Over the last couple of years, however, some enterprises have grown weary trying to manage dozens or even hundreds of separate vendors. Last week Battery Ventures' Max Schireson predicted that trend would accelerate in 2024, writing "the long march towards best-of-breed, where each specialized solution was viewed as a competitive advantage, now feels like a night of too-hard partying; and technology users have a headache from the complexity hangover."
But companies selling integrated stacks of software overcorrected when chasing their smaller rivals by rushing out new features every quarter, Companieh said.
"SaaS platforms, in particular specialized SaaS platforms, are moving faster than most companies can consume the change," she said. Through a series of conversations with companies like Workday and Salesforce, Companieh is trying to get them to focus on slowing down to focus only on services they intend to support in the long run. "That's going to be an interesting pivot for most of these companies."
On the infrastructure side, Cushman & Wakefield still manages a small number of its own data centers. But it is a heavy user of Microsoft Azure across most of its core application stack, including its initial forays into generative AI. It is using Azure OpenAI to access GPT 3.5 and Azure AI search for vector queries.
"AI is kind of like home decor; what works for one company will not work for another," Companieh said. "We're starting in small pilot arenas and scaling incrementally from there, versus making the widespread assumption that we can do anything at an enterprise scale right out of the gate."
Tom Krazit has covered the technology industry for over 20 years, focused on enterprise technology during the rise of cloud computing over the last ten years at Gigaom, Structure and Protocol.
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