Alexander Dreiling of SAP Research in Brisbane, Australia, has posted on a great prototype called Gravity that uses Google Wave to collaborate around business process.

Gravity is a Google Wave “gadget” that can be added within the Google Wave client. It lets participants in a wave use the business process modeling functionality of SAP Business Process Management collaboratively, in near-real time. David Cook called it “the best business example of Google Wave, period!”

The demo shows the result of a merger of a bank and an insurance company. They now need to restructure their business processes and capitalize quickly on cross-selling opportunities between banking and insurance, and a variety of different expertise across the new organization is needed to model the new process flows, both from business and IT.

As they build the model, the additions from each modeler are color-coded, and the process is documented using the Google Wave tools. A Google “robot” is used to check the model for syntax, and the result is exported in industry-standard BPMN 2.0 XML.

The prototype was featured at the SAP TechEd event in Phoenix this week, and one team at the Business Process Design Slam event have posted on their experience of using the tool, using it to automate business processes related to forming a virtual community-based power plant made up of resident’s personal solar wind generation.

The idea is to describe a process that allows a homeowner or business to come online as a micro generator within a township and the various steps (human and automated) that are required. Sustainability gets better over time, the more neighborhoods choose to generate power from green sources to supply the very power this neighborhood consumes – and in pretty much the same timeframe. This also reduces the losses of transporting power over longer distances.  Thus, power companies will more and more become brokers, and less actual suppliers of power.

…you are in a contract with the ‘virtual power plant’ and you can either be within the parameters of the contract and receive the good rates, or go above your contracted power consumption and must pay additional fees. (This can be due to a couple of things, you have bad weather and do not produce enough power and now must consume power at a higher rate. Or for certain reasons you must consume more power than previously contracted, because you have guests in town and must run your a/c on high). At this point, you can continue your contract, or go back and re-contract your plan. (Similar to a cell phone company where you can re-adjust your plan after several months of going over your minutes)

Here’s a glimpse of the process-building experience:

More on SAP and Gravity:

• Sandy Kemsley, SAP Research Overview
• Jevon Macdonald, How Social is the Future of SAP?
• eWeek, Messaging and Collaboration: Nine Google Wave Prototypes

And this is clearly only the start. Analytics, flexible business-oriented process modeling, and collaboration platforms makes for a very powerful combination. Every business process starts with conversations, and get improved through analysis and collaboration. When executives hear about “social networking”, it sounds to them like an expensive, time-wasting alternative to the company picnic, but it’s really about just about making the existing conversations and interactions of employees quicker, easier, and more productive. The Gravity prototype is clearly a great first step in that direction.

Finally, following on from a previous post on Google Wave and SAP, here’s Daniel Graversen duing a presentation about SAP and Google Wave, from the SAP Virtual Community Day sessions hosted by Craig Cmehil

IDC recently released several reports on business analytics market shares, including business intelligence and performance management:

• Worldwide Business Analytics Software 2009 – 2013 Forecast and 2008 Vendor Shares, IDC #219383, August 2009
• Worldwide Financial Performance and Strategy Management 2008 Vendor Shares: Market Consolidation Drives Domination, IDC #218656, June 2009
• Worldwide Business Intelligence Tools 2008 Vendor Shares, IDC #218598, June 2009

You’ll have to subscribe to IDC’s excellent service to get the full details, but if you look carefully through industry articles and vendor samples of the reports you can get many of the key figures and information about how IDC divides up the analytics market.

Here’s my interpretation of the big picture trends:

1. It’s a race between Oracle and SAP. IDC divides the analytics market into three main areas, all roughly the same size (there is also a fourth area, Spatial Information Analytics, but this makes up only around 3% of the overall market)

• Performance management and analytic applications (SAP #1)
• Business intelligence tools (SAP #1)
• Data warehousing platform software (Oracle #1).

Both Oracle and SAP are growing faster than the market average, implying consolidation around the market leaders (although some of the top growth figures came from some of the smaller vendors in the space).

2. Oracle’s lead is narrowing, with SAP is coming on strong… Oracle leads the overall analytics market by IDC’s definition, but Oracle’s growth has slowed since last year, while SAP’s has increased. Oracle is losing market share in its traditional area of strength (data warehousing platforms) where the #2 and #3 (IBM and Microsoft) both grew faster. SAP is growing faster than Oracle overall and in each of the three main areas.

3. …Particularly in FPSM. Thanks to the acquisition of Hyperion, Oracle has been the leader of what IDC calls the Financial Performance and Strategy Management Applications market (part of the analytic applications area) since 2006. But some key acquisitions by #2 SAP (including Pilot and Business Objects) have narrowed the gap considerably, and SAP experienced almost 3x Oracle’s growth over the last year.

Are the Numbers Accurate?

It’s human nature to assume that any set of numbers is more trustworthy than simple rankings. But just how accurate are the numbers, really?

IDC puts a lot of effort into gathering and interpreting the market share figures, and takes a lot of care to allocate the total vendor revenues among the various markets in which they participate. Despite this, there are at least three reasons that the numbers they provide are necessarily inexact.

• First, the numbers can never be more than IDC’s “educated guesses.” Companies that cover multiple market segments almost never publicly break out revenue according to IDC’s groupings, and so are not allowed to provide them selectively to IDC. IDC works with the vendors to try to ensure that there are no obvious mistakes, but there’s an incentive for vendors to try and influence the numbers in their favor (e.g. they may try to persuade IDC that some of the revenue from an area where they are a clear leader should instead be allocated to an area where they are the #2, making them the #1 in both markets).
• Second, even the vendors may only have a hazy idea of the exact revenue that comes from each area. Companies typically purchase related products from vendors in a single deal, and then haggle over the discount amounts. And a single vendor “product” may bundle elements from several different IDC categories. The allocation of the final deal amount between the different components (for example, a database, a data warehouse, some BI tools and some financial planning and budgeting tools) can vary over time, and may be different for different companies. Public companies have to respect some limits set by the SEC concerning revenue recognition, but private companies have a lot of discretion when it comes to stating their revenues (and this does not just concern the smaller vendors — SAS, the #4 vendor overall, is privately held).
• Third, different vendors sell through different channels. If a company sells directly to the final customer, the market share is the same as the revenue, but if it sells through resellers (who make a margin), the real market value of a product may be under-represented by the revenue reported by the vendor. This isn’t technically an inaccuracy, since IDC is explicitly measuring vendor revenues, but it makes it harder to interpret what the numbers actually mean.

Overall, these are marginal concerns, and the overall rankings are probably correct, but I would love to see IDC provide estimates of margins of error directly within the reports, making it easier to know whether small differences are in fact important.

Does Top Market Share Mean that the Vendor has the Best Products?

What do the market share numbers actually mean? What do they imply? What action could or should be taken based on them?

Obviously the vendors and their shareholders care about who’s selling the most (although even then share price typically depends more on profitability than overall revenue). But should anybody else?

Typically, a claim of having the top market share is used to imply that the products are the best ones available in the market (and that is why they are selling so well). But is it true?

Well, yes, they probably are – but in the same way that the #1 in the music charts represents the “best music”.

Just as the top-selling music has the broadest appeal, the leaders have the most broadly useful products. However, just as your own musical tastes might involve something more niche, it may be that a niche BI product or analytic application may be the best for any particular project (which is why there will always be small, focused vendors in the space).

However, the analytics choice most organizations have to make is akin to having to choose the music that will most appeal to all of the different employees in your organization, rather than the music you personally like best. This means most organizations probably shouldn’t choose niche products, because of the value of being able to combine information across different project silos, and because people need multiple different types of access to information.

For example, a sales manager may need a dashboard to track key sales metrics, an OLAP tool for budgeting, an analysis tool for investigating the sales pipeline, and some regular HR reports about team vacation planning. And she would like the data in these reports to be consistent from one usage to another, even when the data in the reports comes from multiple different systems and platforms.

Different products from different vendors may be the “best” niche solutions for each of these needs, but forcing the sales manager to use four unrelated systems, and cope with the inevitable data differences between them, is unlikely to be the best real-life solution. And of course, it’s typically more expensive to deploy multiple solutions than different front ends from the same vendor.

It’s also worth noting that the major vendors may also provide the best niche solutions in many cases, since they typically became major vendors by having the best products in the first place, or grew through the acquisition of other best-of-breed vendors.

So one reason that vendors emphasize market share is because it’s at least somewhat correlated with product quality. Most organizations do a thorough evaluation of the tools available in the market before choosing, and the majority of transactions are extensions to existing deployments, so market share is in some ways the most extensive “customer satisfaction survey” you will ever see. And rather than just ticking boxes, companies and individuals actually have to back up these judgments with money and their reputation.

Other Advantages of Market Share

In addition, choosing a product from a larger vendor provides some tangible benefits above and beyond the quality of the products themselves:

• More support for a wider set of architectures and interfaces. There are economies of scale for supporting different platforms, and larger vendors are likely to have more resources for keeping up with the latest versions of the systems that make up your core information environment, and tighter technical relationships (such as getting earlier access to the next generation of new products). Smaller vendors are typically forced to concentrate on a particular platform or environment. This is of course fine if your environment is supported, but not if you have a complex environment, or may need to change in the future.
• Worldwide services and support. Larger vendors are more likely to be able to support your local language and support requirements. Again, this would not apply to a small vendor in your country who is working in your language, but may be a problem if you need to span geographic locations now or in the future.
• Vendor ecosystem. The success of BI projects are about more than just technology. Larger vendors typically have a more extensive network of consulting and training partners, more other companies you can talk to about using the tools, and higher availability of employees with skills in the vendor’s technology.
• Less risk. The market is undergoing consolidation, and smaller vendors are more likely to go out of business, or be acquired.

There are certainly factors that could also argue in favor of smaller vendors. For example, they may be more responsive, since you represent a larger part of their business, or more innovative, since they have a smaller installed base to maintain, and a stronger incentive to innovate in order to be able to win deals against the bigger players. And they may be more open, with less incentive to tie you to additional products in the vendor’s portfolio (but by the same token, they make be less integrated with the other tools that do you have).

On average, software markets typically consolidate around a small number of larger organizations, showing that in the long run the benefits of size outweigh the potential downsides. And the fact that purchasers don’t want to take “risks” with smaller vendors and that this “winner takes all” trend is firmly embedded in the consciousness of corporate buyers everywhere makes it even more of a self-fulfilling prophecy.

Which Vendor is the Leader?

What does “market leadership” refer to? Is the “leading” product the one with the biggest market share? Or the highest quality? Or the the highest growth? Or some combination of the above?

Clearly, the term is open to interpretation, and vendors often spend considerable effort to find a marketable leadership claim – even to the extent of trying to tailor or invent market segments in which they are the leader (for example, Arbor software essentially invented the “OLAP market” as part of their marketing plans).

Despite much cynical eye-rolling from customers, it seems clear that these claims will always be part of the marketing landscape, since most of us do indeed want to be able to say we chose the “best” or “leading” software for our organizations.

For example, Oracle places ads such as the one on the right in magazines and airports around the world, claiming leadership in Enterprise Performance Management.

But SAP insists it is the #1 in the space, based on its leading share of the analytic applications market, which includes financial planning and strategy management (IDC does not use the term EPM).

According to IDC’s figure, Oracle is not #1 in business intelligence, and probably not in operational analytics (since SAP is leader in both applications and analytic applications). So what is the basis for the claim in the ad?

Oracle provides a link to a web page that attempts to back up the assertion, and which doesn’t mention market share at all. Instead, it links to reports from analyst companies like Forrester and Gartner that use more qualitative measures of “leadership” (interestingly, SAP could probably use the same list of reports to argue it was the overall leader).

Conclusion

Overall, market share is an important criteria that should not be ignored in purchase decisions. You can absolutely have great analytics projects with tools from smaller vendors. And successful analytics is much more about people and process than it is about technology, so in theory you can succeed with any tool.

But the whole point of analytics is that it must evolve over time, and adapt quickly to any changes in your business, and integrate with other systems inside and outside your organization, and I believe this gives the advantage to the larger vendors.

Among the larger vendors, does it matter which is #1 and #2? To SAP and Oracle, yes. For everybody else, it’s just one factor to consider, along with functionality, fit with your architecture, and – of course – cost.

Some new research has been published on the EngagementDB web site on how social media engagement correlates with revenue and profit for the 100 Best Global Brands as measured by BusinessWeek and Interbrand.

The report, The world’s most valuable brands. Who’s most engaged?, attempts to measure the financial worth of social media activities of top brands, including SAP.

The study summarizes brand engagement into four categories:

1. Mavens, such as SAP, with dedicated teams and high engagement across multiple channels
2. Butterflies, present in many channels, but not highly engaged
3. Selectives, with high engagement in a few channels
4. Wallflowers, who are just dipping their toes into social media

The report then looked at the correlation between these categories and financial performance. Interestingly, revenue seems to be correlated with the number of channels (so butterflies do better than selectives), but profits are correlated with engagement (so selectives do better than butterflies).

Of course, correlation is not causation, so while the relationships were statistically significant, the data may just be showing us what we’d already expect: that larger companies simply tend to engage in more media channels, that successful, profitable companies tend to have better engagement with their customers, and that companies have integrated social media into their existing strategies.

The report give case studies of the activities of various top brands, including a report on SAP’s successful social media communities for technical and business customers, SDN and BPX:

The researchers conclude:

While much has been written questioning the value of social media, this landmark study has found that the most valuable brands in the world are experiencing a direct correlation between top financial performance and deep social media engagement. The relationship is apparent and significant: socially engaged companies are in fact more financially successful.

There’s also a blog posting that summarizes the results and gives some tips for greater engagement, and shows the top ten companies for engagement. SAP comes in at #9:

1. Starbucks (127)
2. Dell (123)
3. eBay (115)
4. Google (105)
5. Microsoft (103)
6. Thomson Reuters (101)
7. Nike (100)
8. Amazon (88)
9. SAP (86)
10. Tie – Yahoo!/Intel (85)

Technology is indeed the answer!

Or at least, that’s what is suggested by a new report from the Economist Intelligence Unit, Staying the course? Technology decision-making in turbulent times. The study shows that the current climate provides a good opportunity to drive through major initiatives, that business leaders are looking to technology as in important instrument to prepare their firms for recovery, and that the key importance of better information systems is to better understand customer behavior.

Key findings of the study, which was sponsored by SAP BusinessObjects, include the following:

CIOs are not losing their place at the table. Where they have gained a voice in major business and technology decisions, CIOs positions are not being undermined as a result of the current economic crisis. Very few survey respondents believe that the influence of CIOs in technology investment decisions will decline in their firm over the coming year. A sizeable minority, meanwhile, expect the CIOs involvement in high-level business strategy discussions to expand.

Opportunistic firms are receptive to renewed technology investment. A large minority (44%) of the firms surveyed say that they will be “on the business offensive” in the coming year, looking for acquisitions or openings to take market share from weakened rivals. These firms are more likely than those adopting a “defensive” stance to consider selective new investment in technology. Investment proposals will not enjoy an easy ride, however. More executives are now involved in the approvals process, and the volume and detail of information required is increasing. Higher rates of return are demanded, and projects with shorter return periods are being favored.

Most firms are averse to suspending existing technology projects. Less than one-quarter of survey participants believe that major existing technology-led projects should be suspended until business conditions improve. Indeed, many believe the crisis presents a good opportunity to drive through such initiatives. Few executives, however, even at growth-oriented firms, believe that now is a good time to launch entirely new IT projects. CFOs themselves support the continuance of major existing projects, but it is unclear how often spending requests in such areas will stand up to competing investment priorities in the business.

The focus of investment continues to be on improving customer relationships. Customer service will remain the priority area for IT investments during the coming year. This is for good reason, as evidence mounts from several sectors that customer loyalty is eroding and customer churn increasing. Information management will also be high on the priority list, especially when it comes to projects designed to improve firms’ understanding of customer behavior.

The full results of the study are available free of charge at www.eiu.com/sponsor/sap/technologydecisions

The results of a survey analyzing the current status of corporate decision-making were announced today, called “In search of clarity: unraveling the complexities of executive decision-making”

The survey of 154 global C-level executives, conducted by the Economist Intelligence Unit (EIU) and commissioned by Business Objects, found that more than nine out of 10 corporate executives admit they are making important decisions on the basis of inadequate information. 

More than half of these senior executives are concerned that they may be making poor decisions as a result of missing information. And a quarter believe that management frequently or always gets its decisions wrong.

These are sobering statistics. We are talking about business decisions that can cost an organization millions of dollars, either through costly errors or through the failure to grasp a competitive advantage.

Despite eight out of ten respondents indicating that data is the most important factor in making decisions, ranking it much higher than the opinion of others, personal intuition, or external consultancy, the research showed that more than half of respondents said that decision-making in their organizations was largely informal and ad hoc, and the the report concludes that:

“Decision-making is at the core of all business activity, as executives set strategy and manage operations by weighing a vast array of factors to arrive at the desired balance of risk and reward. It is cause for alarm, then, that executives themselves perceive the quality of decision-making at their companies as mixed at best.”

At a time when the economists are predicting that the current credit squeeze is likely to impact the business environment, it is important to wring out every advantage amidst intense and global competitive pressures.

The simple fact is that executive decision makers are not getting the data they value and need, and most executives, like ourselves, are relying more on “gut instinct” than metrics.

But, why would gut feel override our desire for proof? For fact?

What is failing us? Is fact-based decision-making too difficult to sustain?

Five Ingredients of Good Decision-Making

The report’s authors identify five ingredients of good decision-making. Obviously, supporting good decisions requires a lot more than technology, but I believe BI can help with each of these…

• High-quality data
• Access to advanced systems and training
• Sound judgment
• Trust
• Flexibility

High-Quality Data

High-quality data is obviously a prerequisite for consistently sound decision-making. The better the data, the less time you’ll spend debating the data rather than the decisions that have to be made, and the greater your understanding of your company, your competitors and your environment, the more you can move from guesswork to making strategic choices.

Here are some of the difficulties organizations typically face getting high-quality data, and what can be done to resolve them:

• Data integration. Executive decisions typically require information from several different computer systems, and organizations frequently underestimate the integration challenges involved. Organizations typically address data integration on a project-by-project basis rather than with a more strategy approach. The result is massive redundancy and poor quality. For faster integration and lower costs over the long term, organizations should invest in a robust data integration platform.
• Data quality. There isn’t an organization on the planet that doesn’t have a data quality problem, but where do you start? The latest data quality technologies can help you answer questions such as “which systems have the worst data quality?” and “where could I get the most value from fixing poor quality data?” To improve executive decision-making, organizations should invest in systems to evaluate, monitor and fix data quality.
• Shared definitions. Effective decision-making requires a shared vocabulary. Investing in “metadata management” technology can help you define and maintain the definitions associated with your key business indicators — and reduce the number of board-room arguments.
• Timeliness. Faster decisions mean higher profits. In particular, organizations are starting to realize the big benefits that can come from investing in integrated financial systems that help them close their books faster. And rather than managing by “looking out of the rear-view mirror”, organizations are investing in predictive analytics.
• Unstructured data. Executives need to be use data from all sources, not just from certain types of databases. It’s increasingly important to be able to extract intelligence from non-structured data sources such as documents or emails.
• Benchmarking and external data. Your own systems will rarely contain all the information you need to make decisions. In order to determine your real performance, and make the right decisions, you need to be able to compare your numbers with the economy, the market, or your competitors. New “information on demand” technology is making this as simple as a click of the mouse.
• Governance, compliance, and risk. Decisions can’t be made without considering risk, and without considering your regulatory environments. Organizations should invest in risk management systems that are tightly integrated with the rest of their financial applications.
• Transparency. Information transparency is key to maintaining high data standards. Executives need to be able to see exactly where the data came from, how reliable it is, how it was defined or manipulated, and when it was last updated.

Access to Advanced Systems… and Training

Access to advanced information systems is crucial to improved decision-making, as is training in helping employees to make full use of these tools. There is no point in spending on new technology if people do not use it.

• Ease of use. Th
  e easier the technology, the more people will use it. The latest BI innovations bring information to the users’ fingertips by making it a seamless part of their existing environments, whether it’s email, a standard productivity application like Microsoft Word or Excel, or a cell phone. In the future, BI will be “ambient” – like ambient lighting, it will bring illumination without calling attention to itself.
• User adoption. The implementation of BI technology should be considered the start of a project, not the end. Better access to data doesn’t provide any benefits – that only happens when business processes change based on the new information. Training must be more than a one-off activity, and encompass all aspects of business change management.
• Standardization. Having a standard BI environment across the organization helps provide economies of scale on all aspects of training and user adoption, and makes it easier to create a community of users that can support less experienced users.
• Competency centers. Organizations should invest in a BI competency center: a team that is dedicated to making the best use of the organization’s information assets, ensuring the right trade-offs between the needs of each department/project and the company as a whole.

Sound Judgment

Decision-making processes, whether formal or not, need to leverage the strengths of human intuition. Data does not run companies; people do.

• Collaboration. Intuition is very important, but it needs safeguards — and one of the best is other people. It must be easy to share data, different interpretations of what data means, and proposed plans to improve the situation. The more information is shared, the more likely it is that bad decisions are avoided.
• Guided analysis and best practice applications. Many decisions have to be made on a regular basis by lots of different employees. Organizations should propose a consistent set of analysis steps in order to help every user make decisions as well as the best analyst.
• Links to financial planning. Business decisions have to be backed up by appropriate business changes, including budgets. Your business intelligence systems should be closely linked to your organization’s financial systems.
• Profitability analysis. Make sure that decisions are being made based on what’s important: profit. After all, there’s no point in maximizing revenue if you’re making a loss on each product.
• Sharing with the business ecosystem. It’s no longer just about your organization. You increasingly need to make decisions based on the operations of the “business ecosystem” of customers, partners, and suppliers. For example, to make sound decisions about quality you may have to share and collect warranty information from your distributors.

Trust

To gain employees’ confidence in management decisions, establishing transparency and trust is at least as essential as a good track record.

• Shared vision. The more widely information is shared across the organization, the easier it is for employees to understand and carry out executive decisions – and to provide critical front-line feedback.
• Linking strategy to execution. Nine out of ten organizations struggle to execute their strategy. One thing that can help is clear scorecards and dashboards that cascade high-level goals into key performance indicators that are tracked for teams and individuals. In particular, this helps make the inevitable tradeoffs between different decisions more explicit and transparent.
• Compensation management. People must not only understand the strategy, but understand why they should follow it. There are few things that are more likely to make employees resist and mistrust decisions than misaligned incentives. Applications exist that help organizations plan and implement optimal compensation management strategies – and track if they’re actually achieving the desired goals.

Flexibility – One Size Does Not Fit All

Approaches to decision-making, and even to the use of data, need to reflect the fact that the world is a diverse place, and one size does not always fit all.

• Standard platform. Letting every individual or group look after its own information needs is a recipe for disaster. A BI competency center should be given the mandate to make the necessary trade-offs between flexibility and standards. In today’s fast-changing business environments, flexibility is achieved most easily with a standard platform but a variety of different techniques and interfaces appropriate for different users and situations.
• Collaboration. Organizations increasingly realize that decision-making is an activity that needs to be opened up to more people in the organization. Top-down execution of fixed strategies is giving way to more flexible, collaborative approaches, and a common “information infrastructure” is an essential enabling technology.
• Service-oriented architectures. Computer systems are moving from monolithic suites to more modular, “services-oriented” architectures. As business intelligence becomes more process-oriented, organizations need the ability to easily share and consume information services that can be adapted by business users without further IT assistance.
• Independence. The more volatile the environment, the more companies need to be able to access critical information fast. Your information systems should be maintained separately from your underlying operational systems, and support any and every environment, and be ready to accept information from new systems – you never know when you might merge with another organization, for example.

Conclusion

Technology is necessary but insufficient condition for good decision-making and performance excellence. Without a solid information infrastructure, and support for financial planning, the best decisions and strategy in the world is unlikely to succeed.