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March 30, 2012 in Business Analytics, Business Collaboration, Business Mobility, Business Performance, Cloud Computing, Financial Performance, Governance, Risk & Compliance (GRC), Information Applications, Information Management, Sales Performance, Social Media, Sustainability, Workforce Performance | Tags: Cloud Computing, Compensation, HR, HRMS, Human Capital Management, human resources, Jobscience, learning management systems, LMS, Mobility, Performance, Recruiting, Research, Rypple, Salesforce, succession, Talent Management, Workforce Analytics | by Mark Smith | Leave a comment
New human capital management solutions are entering the market, aiming to simplify recruiting, hiring, onboarding and managing employees. Many such applications focus on talent management for use after employees are hired, but vendors also need to streamline tasks for recruiters, HR administrators and hiring managers. Jobscience provides software that simplifies the processes of getting the talent you want to hire ready to work as quickly as possible.
Jobscience provides a suite of applications that cover recruiting, onboarding, learning and managing of employees. The company uses a foundation of Salesforce.com CRM applications and translates those applications for the needs of human capital management. For example, a marketing application is like sourcing candidates, a sales application is like recruiting candidates and the service application is like managing employees in human resources. Jobscience‘s application suite the TalentCloud has a set of key applications such as RecruiterDesktop, Manager Desktop and Employee Portal that take this approach.
I like what Jobscience has done in recruiting, including linkage to social media, which is a critical place to access potential talent. Our benchmark research into social recruiting found that integration into places like LinkedIn is the most important social media channel for half of organizations and is used on a daily and weekly basis more often than any other source. Jobscience’s integration with LinkedIn addresses the demand that our research found from more than half of organizations to change how they recruit over the next year, and their number one factor is to identify new talent pools.
JobScience TalentCloud2, released in November, brings many points of advancement. In recruiting it has expanded creating job applications,searching and, as I already mentioned, its Apply with Linkedin capabilities. It adds capabilities to create forms that can be used for a range of surveys for input of critical employee-related information. Jobscience also extended its partner framework in its Application Exchange to help drive further integration with its applications in social networking, recruiting, HR and general employee productivity areas.
The software also provides automatic tracking of Equal Employment Opportunity data to help ensure proper compliance. Once a candidate is deemed hired, Jobscience provides simple onboarding capabilities using a central population of information on the candidate that includes tax, benefits and company policy information. For existing employees or to transition a candidate toemployee, the core HR software provides many places to service employees, and has position management capabilities, with a common place for job roles and definitions that can be centrally managed. That’s part of the way the software addresses the need for employee master data management, which our research still finds a big issue in streamlining HR tasks. It also helps ensure that employees take the right level of regulatory and company training, and with more than 30,000 training titles to pick from, it can help ensure that an organization has mitigated any risk of actions or issues in the organization. Because Jobscience uses Salesforce as its platform and technology provider, it can take advantage of that suite’s support for mobile technology, and of Salesforce Chatter for social networking and collaboration.
By partnering with Salesforce.com and using its cloud computing platform and applications as the basis for its solution, Jobscience eliminated a significant amount of R&D work. Jobscience can embrace other advancements that Salesforce brings to market, from integration of social networking technology like Chatter to using its analytics and reports. And organizations can build additional applications in Force.com that can be used in conjunction with Jobscience. Organizations can also look at the broader set of applications that are part of Salesforce Appexchange to connect a series of cloud-based applications. A good example of further integration is the way Jobscience integrated with Dinero for expense management; the solution utilizes each employee’s manager information to gain approval and integrate into the workflow of approval and review. However, Jobscience must improve its workforce analytics which use on Salesforce’s capabilities, which lack the flexibility and sophistication that are required to address what our workforce analytics benchmark has found to be one of the most important areas of improvement for HR.
Unfortunately, public support for Jobscience from Salesforce has been limited. The company seems to think that its acquisition of Rypple will help it address the broader talent management market. While Rypple has value for social recognition and collaboration for achieving goals and tasks within the context of performance management, it is nowhere close to offering what Jobscience has in its solutions as I just assessed (See: “Can You Trust Salesforce and Rypple for Performance Management?”). Salesforce customers have voted for Jobscience as the best recruiting and HR application in Appexchange for more than three years. When you consider the number of organizations whose sales and customer service teams use Salesforce, it’s obvious the benefit of a connection to recruiting and hiring talent and providing employees with tools to improve their skills. Salesforce should promote Jobscience to gain better credibility in the market and to have a better foot into human capital management. Jobscience should also communicate the value of its approach for customer service and sales organizations that use Salesforce in order to gain more entry points for its recruiting and onboarding offerings.
For some people, Jobscience is a new name in human capital management, but it is actually a proven provider helping to extend the science of recruiting and managing employees. This company has been operating for more than a decade, and has more than 300 customers and has helped in the recruitment of more than half a million jobs. Lately Jobscience has begun to get more aggressive in its marketing; it recently offered Taleo Business Edition customers a path and incentive to migrate, since it is not clear how much of a priority that software will be with Oracle’s acquisition of Taleo, as I have already discussed.
As outlined in our public research agenda, the goal of recruiting and retaining talent and empowering employees with mobile and social capabilities and a common place for workforce information should be at the center of every HR organization’s mission. Jobscience’s approach to extending its applicant tracking software to social media channels is the top software approach found in 49 percent of organizations. Its applications’ simplicity and usability and its use of cloud computing makes it easy for organizations to sign up and get started. Jobscience is worth a closer look.
Mark Smith – CEO & Chief Research Officer
March 27, 2012 in Business Analytics, Business Intelligence, Customer & Contact Center, IT Performance, Sales Performance, Social Media, Supply Chain Performance, Workforce Performance | Tags: Business Analytics, Business Intelligence, Data Scientist, Predictive Analytics | by Ventana Research | Leave a comment
As a technology, predictive analytics has existed for years, but adoption has not been widespread among businesses. In our recent benchmark research on business analytics among more than 2,600 organizations, predictive analytics ranked only 10th among technologies they use to generate analytics, and only one in eight of those companies use it. Predictive analytics has been costly to acquire, and while enterprises in a few vertical industries and specific lines of business have been willing to invest large sums in it, they constitute only a fraction of the organizations that could benefit from them. Ventana Research has just completed a benchmark research project to learn about how the organizations that have adopted predictive analytics are using it and to acquire real-world information about their levels of maturity, trends and best practices. In this post I want to share some of the key findings from our research.
As I have noted, varieties of predictive analytics are on the rise. The huge volumes of data that organizations accumulate are driving some of this interest. Our Hadoop research highlights the intersection of this big data and predictive analytics: More than two-thirds (69%) of Hadoop users perform advanced analytics such as data mining. Regardless of the reasons for the rise, our new research confirms the importance of predictive analytics. Participants overwhelmingly reported that these capabilities are important or very important to their organization (86%) and that they plan to deploy more predictive analytics (94%). One reason for the importance assigned to predictive analytics is that most organizations apply it to core functions that produce revenue. Marketing and sales are the most common of those. The top five sources of data tapped for predictive analytics also relate directly to revenue: customer, marketing, product, sales and financial.
Although participants are using predictive analytics for important purposes and are generally positive about the experience, they do not minimize its complexities. While now usable by more types of people, this technology still requires special skills to design and deploy, and in half of organizations the users of it don’t have them. Having worked for two different vendors in the predictive analytics space, I personally can testify that the mathematics of it requires special training. Our research bears this out. For example, 58 percent don’t understand the mathematics required. Although not a math major, I had always been analytically oriented, but to get involved in predictive analytics I had to learn new concepts or new ways to apply concepts I knew.
Organizations can overcome these issues with training and support. Unfortunately, most are not doing an adequate job in these areas. Not half (44%) said their training in predictive analytics concepts and techniques is adequate, and fewer than one-fourth (24%) provide adequate help desk resources. These are important places to invest because organizations that do an adequate job in these two areas have the highest levels of satisfaction with their use of predictive analytics; 89% of them are satisfied vs. 66% overall. But we note that product training is not the most important type. That also correlated to higher levels of satisfaction, but training in concepts and the application of those concepts to business problems showed stronger correlation.
Timeliness of results also has an impact on satisfaction. Organizations that use real-time scoring of records occasionally or regularly are more satisfied than those that use real-time scoring infrequently or not at all. Our research also shows that organizations need to update their models more frequently. Almost four in 10 update their models quarterly or less frequently, and they are less satisfied with their predictive analytics projects than those who update more frequently. In some ways model updates represent the “last mile” of the predictive analytics process. To be fully effective, organizations need to build predictive analytics into ongoing business processes so the results can be used in real time. Using models that aren’t up to date undermines the whole effort.
Thanks to our sponsors, IBM and Alpine Data Labs, for helping to make this research available. And thanks to our media sponsors, Information Management, KD Nuggets and TechTarget, for helping in gaining participants and promoting the research and educating the market. I encourage you to explore these results in more detail to help ensure your organization maximizes the value of its predictive analytics efforts.