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My colleague Mark Smith and I recently chatted with executives of Tidemark, a company in the early stages of providing business analytics for decision-makers. It has a roster of experienced executive talent and solid financial backing. There’s a strategic link with Workday that reflects a common background at the operational and investor levels. As it gets rolling, Tidemark is targeting large and very companies as customers for its cloud-based system for analyzing data. It can automate alerts and enhance operating visibility, collaboratively assess the potential impacts of decisions and support the process of implementing those decisions.

Tidemark’s product fits into the performance management/decision support category but has several points of differentiation. One is that it enables larger enterprises to work interactively with a broad set of operating and financial metrics rather than working with multiple legacy business intelligence and reporting systems. It can integrate enterprise data from ERP, CRM, supply chain, logistics, maintenance, real estate and other systems into a single cloud-based analytic and data store in a way that ensures there is master data control from source systems to the new warehouse, and that uses common semantic-layer definitions consistently across all processes and systems.

The business purpose of marshalling all the data in one place is to take advantage of recent advances in managing large-scale data using new database techniques that we have assessed. This can lower the cost of doing so along with utilizing in-memory data processing, which makes it feasible for large organizations to work with operational and financial information much more interactively. Because this can reduce the time required to assemble information (in reports and dashboards), organizations gain time to focus on making the right decision and implementing it. Rather than struggling to lash together sets of fragmented and siloed data every time a new set of analytics is needed, the right data in the right format and context is available at any level for various purposes, including integrated business planning, predictive analytics, and analysis of trends, cost-to-serve metrics, customer profitability and  product profitability. The same data set can be used for dashboards, performance scorecards and operational risk measurement and management. Executives, managers and analysts can go beyond drilling down into the details of what just happened. For example, they can do real-time collaborative contingency planning to explore in detail the impacts of several courses of action during a one-hour meeting.

Tidemark’s second point of differentiation is to make the user experience as close to that of a consumer application (and as far away from traditional business software) as possible. Design has become an increasingly important element in industrial products once sold mainly on functional considerations instead of usability. I expect the same is finally coming true in software as past limitations to design melt away with advances in the underlying technology. I also put tablet and mobility support in this category, because these have become table stakes for enterprise applications. An individual vendor’s advantage in mobility may be built initially on technical capabilities, but competitors can quickly replicate it. User interface design, however, can be a source of lasting advantage.

Tidemark has elected to use HTML5 Internet technology standard so it can support as many Web browsers, smart phones and tablets as possible. In this respect, I think executives decided that the underlying technology is a commodity and therefore it’s best to embrace a broad standard. This may prove to be a smart bet or it could be a sticking point since it will not use the native capabilities of mobile platforms. Notably, it will not be part of the Apple ecosystem, which I think may hurt Tidemark today but may be of no consequence in the future.

Another new, consumer-like feature is the visual metaphor of using sentences to describe what you are doing and seeing with business analytics, which adds to usability for business people. In this form,  analysis, planning and review activities fit the rhythms of how people naturally do and think about business. This approach makes it simple to understand what a business user is asking from the system and what it has presented.

A third point of differentiation from standard performance management offerings is having advanced analytics integrated into the application. Because comprehensive real-time and near-real-time finance and operations data are available for in-memory processing, it’s feasible to employ predictive analytics to improve forecast accuracy and to provide a comprehensive range of alerts when results diverge materially from what’s expected. Such a structure facilitates creating driver-based models for planning and budgeting. Moreover, Tidemark includes risks in its scorecard presentation. All business decisions involve risk, yet risks are rarely part of a balanced scorecard. Scorecards are balanced precisely because they cover trade-offs (for example, in a call center, balancing time-on-call with first-call resolution). Although some risks are implicit in every item on a scorecard (that is, not achieving a key objective) others are indirect or less than obvious, such as deferring scheduled maintenance or operating above capacity limits to accommodate unexpected orders. That noted, it’s impossible to say, based on this introduction, just how broad and deep Tidemark’s capabilities (especially industry-specific metrics, advanced analytics and risk measures) will be in the initial release. Operational risk analytics are likely to be elementary because, outside of financial services, that is the (sad) state of the art at this moment.

It’s still early days for Tidemark, so file the comments above under “excellent if true.” There are a number of big potential snags that the company and its users may confront when they put their system in place.

First on the list are the performance and scalability proof points that must be demonstrated in full-scale deployments. I’m not sure this will be a big issue since the basic technology foundations (cloud data and applications, in-memory processing and core analytics) that Tidemark rests on are solid. More likely, the challenge to users and Tidemark will be the snags that are inevitable when dealing with large organizations’ IT infrastructure (nonstandard legacy systems, for instance) as well as the maintenance issues that companies will have to address that might cause performance and other system metrics to fall short of what customers are expecting. Or performance may be adequate for most complex analytical tasks but not for, say, organizations that do complex sales and operations planning involving large numbers of rapidly changing stock-keeping units (SKUs). At this point, I doubt any of these issues will prove to be overall showstoppers, but they may limit the software’s appeal.

A more fundamental issue that I see is whether and to what degree companies will change how they operate to take advantage of the technology available. Just because something is technically feasible doesn’t mean that companies will change old ways of doing things. Our research shows few companies (just 6%) use driver-based plans, which, from a practical standpoint, is the only way to be able to do agile planning. Outside of financial services, few companies understand how to measure and manage operational risks beyond those major that are already incorporated in business reviews (such as failure to meet sales and profit targets). Attenuating the impact of unfavorable events collaboratively with established risk mitigation scripts (something that is feasible in Tidemark) is not well practiced outside of the military or the parts of companies facing heavy safety and health liabilities.

The next fundamental issue is data governance. As I look at it, the initial system setup can, with varying degrees of difficulty, overcome the accumulated impact of sloppy data management practices. Thereafter, there can be considerable cost involved in maintaining the integrity of the comprehensive data unless the company is rigorous about data governance.

The last fundamental issue for some companies may be the total cost of ownership. Tidemark’s initial pricing projections are competitive with on-premises systems. Companies with sprawling, disjointed enterprise system infrastructures and poor data stewardship probably will have to spend quite a bit more both up front and for ongoing maintenance for a system that includes data from a broad set of enterprise systems. Since few companies have mature data governance practices, dealing with data issues may prove to be a big cost factor in regards to time and agreement on the definitions and representation.

On balance, my initial impression of Tidemark is positive. There’s a great deal of promise and more than a few things that its established competition might want consider copying. Stay tuned.

Regards,

Robert Kugel CFA – SVP of Research

At its annual Influencer’s Summit in Boston, SAP offered multiple perspectives on where the company’s strategy and products are heading. Overall, I was struck by the essential similarities to its message on its strategic direction a decade ago. The overarching objective in its roadmap now, as then, is to have information technology increasingly adapt to the needs of individual users and how they choose to execute established/repetitive or ad-hoc processes,  rather than forcing them to adapt to the limitations of the technologies they are using. Back then the idea was to create a comprehensive process framework – a closely coupled approach. Today, it’s essentially the opposite, as SAP products run on an architecture that enables flexibility – a loosely coupled approach – both in how the computing infrastructure is organized and how people execute their tasks. It seems to me that this reflects the impact of having choices between cloud-based software as a service (SaaS) and on-premises systems and the need to enable access through a variety of devices (from desktops to mobile handhelds and tablets). Mobility is important both for people whose roles take them beyond the firewall (in sales, service and logistics, for example) and executives and managers who often find themselves managing by walking around. Tablets, smartphones and similar devices are attractive also because people consider them personal items and associate them with fun, whereas desktops and notebooks are corporate and work-related.

Architecture drives product design, and SAP continues to stress HANA and the ability of its in-memory system to expand the scope and capabilities of applications that run on it. That makes sense since any in-memory computing platform can transform how software is used. The challenge then becomes transforming the habits of users. For example, I’ve noted the need for more contingency planning. One reason it’s not used more is that the latency between thought and answer in complex scenario analyses on disk-based systems is often too long to be useful in promoting a collaborative dialogue around possible situations and their potential outcomes. “Too long” is a relative thing, of course, but based on my experience, the outer edge in this case may be 10 seconds to 1 minute. Once the technology foundation is in place, the hard work begins. Companies have to understand what is technologically feasible and that they need to adopt better planning techniques, notably driver-based planning. From my perspective, few technology advances have immediately led to forehead-slapping, “aha!” moments. Thus the spread of adoption of in-memory technology into business processes is never automatic, so one of SAP’s challenges is to create demand for HANA by promoting improved management techniques that are supported by in-memory computing. So the technology is different, but the business issue is much the same.

Since it offers differentiation in an increasingly commodity-like business computing product market, advanced analytics was a key theme at the summit. Analytics are an increasingly important capability for organizations, enabling companies to manage more effectively, not just efficiently. Predictive analytics, for example, should play a role in more than the 13 percent of organizations that our research shows are using them. They have become much more accessible but aren’t well understood. Predictive analytics certainly help in forecasting, but they’re also handy for spotting exceptions from expected results, especially when companies have to work with large data sets. Departures from expected results can provide the basis for management alerts and notifications, as when an order from a regular customer or an invoice payment is not received within the normal period. Both situations can indicate customer issues. A follow-up to the former might uncover that a competitor is offering promotional deals to gain market share, and the company could counter the move sooner. The latter might be the result of some issue that occurred in fulfilling the order, in which case it would be better to have the first communication with the customer be an immediate note of concern rather than a dunning notice weeks later. Analytics is an important theme in business computing, and SAP will need to focus on it in its product efforts.

Risk management is yet another area where real-time data can be an important enabler of capabilities that are not practical without the ability to crunch substantial amounts of data rapidly. Outside of financial services, few industries manage risk comprehensively, and even financial services can put more of their operations into a risk management framework. In part this situation reflects the fact that few industries have developed a framework for measuring risk objectively. Part of this is historical: Financial services have always been about numbers, and it’s straightforward to use these numbers to measure risk. Financial ratio analysis therefore can be applied to assessing many operational risks in that industry. And since it was one of the first to utilize computers to handle operations, these corporations have long experience in using software to manage risk. By contrast, only within the past few decades have other types of companies begun using IT systems to manage operations. Using data to identify and track operational risks is still nascent, so any discussion of how far it has developed strikes me as premature. Yet I believe risk management in consumer, industrial and business services should be on the radar screens of executives, especially because it addresses the agency dilemma. SAP’s risk management software portfolio could expand substantially over the next several years to address the need. (I expect the same from Oracle and IBM, along with many smaller vendors.) But here again businesses must become aware of the need before a market will grow.

SAP Business ByDesign is a topic worthy of its own blog, so I’ll post one on this topic shortly.

It struck me that this Influencer Summit demonstrated SAP’s understanding of what it needs to accomplish over the next few years to be competitive with its substantially larger rivals – IBM, Oracle and, in applications for small and midsize businesses, Microsoft. Strategy is one thing but execution – as ever – is probably more important. Here, SAP must demonstrate that it can operate at faster clock speed than it has in the past to maintain its top-tier position in business computing.

Regards,

Robert D. Kugel – SVP Research

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