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vr_SF12_07_impediments_in_sales_motivate_investmentIn an analyst perspective at the beginning of this year I wrote that sales organizations must step beyond conventional wisdom to generate the best outcomes. One such step is to invest in software that delivers immediate value to manage sales and be efficient in its operations. Our latest research on sales organizations finds that inconsistent execution (53%), scattered information (48%) and limited visibility (42%) are motivating investment to improve sales. At CompCloud, its annual conference, Xactly unveiled advances in its software to help improve the effectiveness and productivity of sales organizations. Spokespeople said the company’s sales compensation products have helped users manage US$10 billion in commissions in the past two years.

To make it easier to access critical information from its applications Xactly now supports the range of mobile devices running native Apple iOS, Android and HTML5 apps. The mobile capabilities enable users to view commission statements, track quota attainment and compare performance to team rankings. Xactly is right to advance its mobile efforts as account managers and management extensively use smartphones and tablets. Our latest research in sales finds that smartphones will be deployed to four out of five (81%) in sales and tablets to three-quarters by the end of 2015.

The company also announced the release of Xactly Quota to help management and analysts allocate quota assignments to teams. By automating the quota process and providing visibility into quota performance this application helps reduce manual effort and potential errors in those tasks. The quota management application can link with Xactly Incent to help users plan sales targets and link potential commissions to payments. They can collaborate in designing and agreeing on quotas, and the comments feature enables direct feedback. Our research finds that quota attainment is the top way to measure overall sales performance, so this feature is likely to please Xactly’s customers and increase sales. After aligning quotas and commissions, the next logical advance would be to help users manage sales forecasts to support progress toward quotas and ultimately commissions. Comparing quotas to forecasts is a top priority for sales teams, according to our research. Xactly’s products can integrate forecasts into its analytics, which is a key first step to assess to quota and potential commission. I have already written that dedicated technology enables successful forecasting.

At the conference I got to review demonstrations of its analytics and benchmarks in Xactly Insights that help provide performance metrics from all the data it collects from its customers. Such measures can be useful: Xactly released a report on performance and quotas showing that 79 percent of sales reps selling software as a service miss their quotas. These insights help provide a guideline to where a company can improve in the design of its quotas which Xactly released a new application but also where it compares in the market to others. Xactly has been able to take the aggregate of its own customers’ metrics in using their products to provide some insightful perspective on a range of compensation and time related sales metrics.

Xactly unveiled Xactly Objectives at its 2013 conference that I covered, and we named it the prestigious 2013 Technology VentanaResearch_TechInnovation_Award_Winner_2013Innovation Award winner for sales. Now the product is fully localized to support Spanish, French, German and other languages. It is easy for managers and sales reps to track progress toward their overall objectives. Having a system to identify overarching sales objectives and link them to sales compensation is important to motivate and guide personnel on a regular basis. The Xactly Objectives can be used anywhere in an organization too, which makes it appealing to any department.

Other improvements outlined at this year’s conference included more comprehensive incentive statements, analytics that can be displayed in any HTML5-compliant Web browser, flexibility in plan rules with lookup tablets and adaptations to credit allocations. Xactly continued focus on satisfying its customers through product improvements have provided it a very high customer retention rate.

Xactly continues to focus on inspiring sales management and operations to making sales more productive and generate higher level of sales. Its software is more appropriate for sales compensation and related processes than CRM or SFA applications and much better than using general-purpose spreadsheets. Our research finds that more than half of sales organizations still use spreadsheets for these purpose and that doing this undermines their ability to manage sales with accurate information. In today’s intensely competitive sales environment, Xactly is positioned to grow. Sales organizations that seek to improve these sales and compensation processes and provide the information that sales teams need both to perform well and be satisfied in their jobs should examine Xactly’s software.

Regards,

Mark Smith

CEO and Chief Research Officer

Many businesses are close to being overwhelmed by the unceasing growth of data they must process and analyze to find insights that can improve their operations and results. To manage this big data they find a rapidly expanding portfolio of technology products. A significant vendor in this market is SAS Institute. vr_Big_Data_Analytics_02_defining_big_data_analyticsI recently attended the company’s annual analyst summit, Inside Intelligence 2014 (Twitter Hashtag #SASSB). SAS reported more than $3 billion in software revenue for 2013 and is known globally for its analytics software. Recently it has become a more significant presence in data management as well. SAS provides applications for various lines of business and industries in areas as diverse as fraud prevention, security, customer service and marketing. To accomplish this it applies analytics to what is now called big data, but the company has many decades of experience in dealing with large volumes of data. Recently SAS set a goal to be the vendor of choice for the analytic, data and visualization software needs for Hadoop. To achieve this aggressive goal the company will have to make significant further investments in not only its products but also marketing and sales. Our benchmark research on big data analytics shows that three out of four (76%) organizations view big data analytics as analyzing data from all sources, not just one, which sets the bar high for vendors seeking to win their business.

In the last few years SAS has been investing heavily to expand its portfolio in big data. Today its in-memory infrastructure can operate within Hadoop, execute MapReduce jobs, access the various commercial distributions of Hadoop, conduct data preparation and modeling in Hadoop and extend it to its data and visual discovery and exploration tools. SAS has architected its analytics tools and platform to use Hadoop’s Pig and Hive interfaces, apply MapReduce to process large data sets and use Hadoop Distributed File System (HDFS) to store and access the big data. To exploit Hadoop more deeply, the SAS LASR Analytic Server (part of SAS Visual Analytics) connects directly to HDFS to speed performance. SAS LASR Analytic Server is an in-memory computing platform for data processing and analysis that can scale up and operate in parallel within Hadoop to distribute the computation and data workloads. This flexibility in the architecture enables users to adapt SAS to any type of big data, especially Hadoop deployments, for just about any scale and configuration. To work with other database-oriented technologies the company has built technical partnerships not only with major players Teradata and SAP but also with the new breed of Hadoop vendors Cloudera, Hortonworks and Pivotal, as well as with IBM BigInsights. SAS also engineered access to SAP HANA, which establishes further integrated into SAP’s data platform for analytics and other applications.

At the Inside Intelligence gathering, SAS demonstrated its new Visual Statistics product. Like its Visual Analytics this one is available online for evaluation. It offers sophisticated support for analysts and data professionals who need more than just a visually interactive analytic tool of the sort that many providers now sell. Developing a product like Visual Statistics is a smart move according to our research, which finds that predictive analytics and statistics is the most important area of big data analytics, cited by 78 percent of organizations. At this point visual and data discovery are most common, but we see that users are looking for more. SAS Visual Statistics can conduct in-memory statistical processing and compute results inside Hadoop before the data is transferred to another analytic data repository or read directly into an analytics tool. A demonstration of these capabilities at the analyst summit revealed how these capabilities along with the use of tools in SAS 9.4 could raise the bar for sophisticated analytics tools for business.

vr_Info_Optimization_04_basic_information_tasks_consume_timeSAS also has a data management software suite for data integration, quality, mastering and governance and is working to make the product known for its big data support. This is another important area: Our research in big data analytics finds quality and consistency of data to be significant challenges for 56 percent of organizations and also that 47 percent are not satisfied with integration of information for creating big data analytics. SAS is expanding to provide data quality tools for Hadoop. Its portfolio is expansive in this area, but it should take steps to market these capabilities better, which spokespeople said it will do in 2014. Our recent research in information optimization found that organizations still are spending disproportionate amounts of time in preparing data (47%) and reviewing it (45%) for analytics. They need to address these difficulties to free their analysts to spend more time on analysis that produces recommendations for decision-makers and to collaborate on business improvement. SAS’s efforts to integrate data and analytics should help reduce the time spent on preparation and help analysts focus on what matters.

SAS also will expand its SAS Stream Processing Engine with a new release coming by midyear. This product can process data as it is being generated, which facilitates real-time analytics – that’s the vr_oi_how_operational_intellegence_is_usedthird-most important type of big data analytics according to our research. Applying analytics in real time is the most important aspect of in-memory computing for two-thirds (65%) of organizations and is critical as SAS expands its SAS LASR Analytic Server. Our benchmark research on operational intelligence shows that the processing of event data is critical for areas like activity or event monitoring (said 62% of participants) and alerting and notification (59%). SAS will need to expand its portfolio in these areas but it is fulfilling on what I call the four types of discovery for big data.

SAS also is moving deeper into cloud computing with support for both private and public clouds through investments in its own data centers. Cloud computing is an increasingly popular approach to building a sandbox environment for big data analytics. Our research finds that more than one-fifth of organizations prefer to use cloud computing in an on-demand approach. SAS will have to provide even more of its portfolio using big data in the cloud or risk customers turning to Amazon and others for processing and potentially other computing uses. SAS asserts it is investing and expanding in cloud computing.

vr_Big_Data_Analytics_15_new_technologies_enhance_analyticsSAS’s efforts to make it easier to work with big data and apply analytics is another smart bet; our research finds that most organizations today don’t have enough skilled resources in this area. One way to address this gap is to design software that is more intuitive, more visual and more interactive but sophisticated in how it works with the primitives of Hadoop; SAS is addressing this challenge. Our research finds growth of in-memory (now used by 42%) and Hadoop (50%) technologies, which will have more impact as they are applied directly to business needs and opportunities. SAS is at the intersection of data management and analytics for big data technologies, which could position it well for further growth in revenue. SAS is betting that big data will become a focal point in many deployments and they can help unify data and analytics across the enterprise. Our research agenda for 2014 finds this to be the big opportunity and SAS is fixated on being the vendor of choice for it. If you have not examined how SAS can connect big data architectures and facilitate use of this important technology, it will be worth your time to do so.

Regards,

Mark Smith

CEO & Chief Research Officer

Mark Smith – Twitter

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