The Competitive Advantage Of SaaS

By Matt Pillar, chief editor

September 2015 Innovative Retail Technologies

As SaaS acceptance grows, the retailers are looking beyond safe “gateway” applications in search of competitive differentiation in the cloud.

While the SaaS model of application delivery has demolished the cost barriers that precluded many small-to-midsize retailers from accessing tier-one software functionality, the market is still exhibiting a cautious approach to the cloud. Here, Shaun Kirby, CTO at Cisco Consulting Services, and David Dorf, senior director of product strategy at Oracle Retail, discuss where SaaS is hot, where it’s not, and pragmatic strategies for SaaS adoption.

Hot Applications For SaaS In Retail
While Oracle Retail currently offers a suite of 17 cloud-based services for retail via its Cloud Commerce offering, Dorf admits that most retailers aren’t ready for them all — yet. “We’re focusing on the SaaS applications that retailers are most apt to adopt, and those are generally the applications that aren’t going to take the business down if there’s a delivery or execution problem,” he says. That equates to ready adoption of SaaS services for discrete and easily implemented applications with well-defined interfaces, such as LP video and analytics, store ops analytics, and inventory lookup.

At Cisco, Kirby is seeing healthy adoption of basic, common business infrastructure such as email, human resources, payroll, and workforce management applications. “Facing continually increasing margin pressure and global competition, retailers are eager to deliver more for less, and SaaS can help retailers both implement more capabilities [such as new shopper experiences or new ways to streamline operations] and cut cost,” says Kirby.

“The growth areas we see on the near horizon are the services necessary to improve the omni-channel customer experience,” says Dorf. “We’re not yet seeing a lot of interest in SaaS-based merchandising applications, because merchandising is characterized by so many points of integration with legacy systems, which raises the level of complexity,” he says. Kirby adds that applications like merchandising, space planning, and especially delivering of new in-store customer experiences are mostly still kept in-house and purpose-built to distinguish the retailer and provide competitive advantage.

Data Access, Analytics Drive SaaS Adoption
In addition to delivery of specific applications, Kirby says retailers are seeking to leverage more advanced analytics and business intelligence applications through SaaS, including sophisticated elements such as machine learning as a service, as the analytics SaaS space matures rapidly. “SaaS-based analytics tools have been growing in sophistication and popularity in recent months. They offer powerful data science toolboxes in the cloud, saving retailers significant time and cost in setting up their analytics environments,” says Kirby.

“The growing repository of analytics algorithms and visualization tools available through SaaS means retailers can look to the cloud for the most comprehensive collection of analytics capabilities.”

"SaaS can significantly reduce time to analytics results that provide a competitive advantage."

Shaun Kirby, CTO, Cisco Consulting Services

Dorf agrees that the agility of data access and analysis afforded by the cloud is fueling its adoption. Leveraging SaaS-based analytics tools, he says, allows retail tech shops to move away from mundane IT tasks and refocus their efforts on real retail work. “SaaS lightens the load on IT by removing the burdens associated with backups, audits, upgrades, and security management. Business insight afforded by SaaS-based analytics tools affords retailers a really good understanding of the data they already have,” says Dorf. “As we add more analytics capabilities via the cloud, we can grant that access more quickly via automatic upgrades, which dramatically reduces the retailer’s time to value.” Because these tools are offered in a pay-only- for-what-you-use style fashioned after the utilities model, retailers can strategically and incrementally build on their data analytics initiatives at their own pace. “Retailers have been sitting on a lot of Big Data for a long time. SaaS-based analytics applies ‘Big Science’ to that Big Data, allowing merchants to finally extract value from it,” says Dorf.

Kirby adds that SaaS environments can also promote greater collaboration with partners, suppliers, and even research organizations to help retailers solve challenging analytics problems more quickly and effectively. “If the retailer can make its data available to the SaaS platform, not only can that data be analyzed with a myriad of tools and techniques, but the merchant can also invite others to analyze the data in order to derive additional insight, or even host an open innovation challenge through a community such as Kaggle [www.kaggle.com],” he says. Other analytics offerings like Wise.io (www.wise.io) or bigml (https://bigml.com) provide tools and APIs to make it easier for retailers to conduct sophisticated predictive analytics quickly. “SaaS can significantly reduce time to analytics results that provide competitive advantage,” says Kirby.

Security: SaaS Versus The Data Center
While some of the leading SaaS providers have compiled impressive records of availability and security of their services, Kirby says this doesn’t mean that they or their retail customers can consider SaaS security complete. “As new threats evolve, SaaS providers will need to stay ahead of the curve and turn to the latest security architectures and approaches, such as pervasive security policies, managed from a unified console with complete visibility across the application suite,” he says. “Security technology maintained only on a central server and attempting to establish a secure boundary around that server are not enough in the era of the cloud and the Internet of Everything (IoE), where more connections to partners and other services are needed.”

With that said, Dorf speculates that retail CIOs are eager to lean on vendor partners for security services, and that SaaS providers that demonstrate holistic approaches to data security are poised to provide that relief. “Retail IT shops are really under the gun to secure their own data centers, because no one wants to have to testify in front of Congress as to why they lost data,” he says. Due to constantly evolving threats, it can be quite expensive to maintain robust security of on-premise data centers, which require near-daily intrusion detection refreshes and constant monitoring to guard against hackers and anomalies. “Security-minded SaaS providers can offer economies of scale that aid the data security effort,” says Dorf. “When we release new SaaSbased software, we comprehensively and continuously scan it for things like port vulnerabilities and SQL injection detection to make sure it’s as secure as possible.”

Next Steps For SaaS
If you think SaaS application delivery — in any of its myriad of iterations — is right for your organization, Dorf and Kirby agree that the first two steps are defining your enterprise architecture and modeling your enterprise data. “Having a comprehensive, mutually exclusive, and exhaustive set of definitions for services, or the reusable building blocks from which more complex applications can be built, paves the way to effective selection of a SaaS offering and establishment of the desired business capabilities on the SaaS platform,” says Kirby.

Dorf cautions retailers not to underestimate the business transformation brought about by a migration to the SaaS model. “When you move to the cloud, you move to a different way of looking at IT. Because it’s a service-based model, it changes the relationship between the merchant and the vendor,” he says. “It requires a comprehensive understanding of integration points and how they’re going to work, and you need to start with an ‘as-is’ diagram to understand that.” That’s where the enterprise data model comes in. “A holistic enterprise information model, defining the entities and their attributes as required to enable all aspects of the business, greatly simplifies migration to SaaS, which could require data mapping and conversion,” says Kirby. Dorf adds that the process presents a great opportunity to perform a data quality analysis to avoid migrating “junk” data into the cloud.

After establishing the enterprise architecture strategy and information model, Kirby advises retailers to consider which SaaS offerings would provide the most value and draft a three- to five-year road map defining the sequence of migration, from basic applications to more specialized. He says key performance metrics should be defined at each stage to measure the effectiveness and value of SaaS to continually improve the road map and plans for future migrations. Dorf says this road map must take the legacy investment into account. “Most retailers have a large investment in on-premise hardware and software. As older systems come up for renewal, merchants should look at the cloud as an alternative and consider what a hybrid approach might look like in their enterprise,” he says.

After establishing the enterprise architecture strategy and information model, Kirby advises retailers to consider which SaaS offerings would provide the most value and draft a three- to five-year road map defining the sequence of migration, from basic applications to more specialized. He says key performance metrics should be defined at each stage to measure the effectiveness and value of SaaS to continually improve the road map and plans for future migrations. Dorf says this road map must take the legacy investment into account. “Most retailers have a large investment in on-premise hardware and software. As older systems come up for renewal, merchants should look at the cloud as an alternative and consider what a hybrid approach might look like in their enterprise,” he says.