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January 31, 2014 in Big Data, Business Analytics, Business Collaboration, Business Performance Management (BPM), Customer Performance Management (CPM), Governance, Risk & Compliance (GRC), Operational Performance Management (OPM), Sales Performance Management (SPM), Social Media | Tags: Compensation, forecasting, Sales, Sales Performance Management, SFA | by Mark Smith | Leave a comment
It should be no surprise for those who work in sales that increasing outcomes collectively is not always easy. Sales teams and individuals work under pressure to perform at high levels, selling more than they did in the previous period or more than the person who previously had responsibility for a territory. Today’s economic and competitive environments demand that everyone work not just faster but smarter in their sales efforts. To excel in this environment requires not just wise use of time but prioritization of the activities and tasks that contribute to achieving the quota and forecast. In the past, sales organizations often resisted adopting new technology, but it’s time for them to realize that tools are available to facilitate better sales performance. As I outlined in the overview of our business and technology research agenda for this year, the sales department has a ripe opportunity to get smarter in how it operates. This is the essential point of our research practice in sales applications and technology: Our methodical benchmark research examines applications and technology best practices and benefits for sales organizations, and we assess the vendors and products in this market through our Value Index ratings. We will start 2014 with the latest release of our Value Index on Sales Performance Management, which will help sales management evaluate products to assist in improving performance of the organization.
Technology advances in sales applications and technology in the last several years have given those who use them an advantage. For example, mobile technology enables sales organizations to quickly access metrics from sales analytics; these can be shared to help the whole team meet their objectives. But these improvements first require willingness to change, to go beyond the conventional wisdom of using sales force automation (SFA) for more than defining and tracking accounts, contacts and opportunities. Those who continue to use spreadsheets to manage sales performance will be even less efficient and fall further behind those who use more capable tools. Our latest benchmark research in sales forecasting shows that more than half (59%) still use spreadsheets to manage sales forecasts; doing so wastes time and prevents immediate access to critical information. It also finds that the process is not reliable and data is not accurate in more than half of organizations.
The imperative to provide the best possible customer experience, which my colleague Richard Snow outlines in his customer engagement agenda, indirectly impacts sales. Both require high-quality and relevant product information whether it comes from sales interactions, e-commerce or websites. Both customer service and sales can benefit from the organization creating a single repository of all product information managed centrally. Tools for product information management (PIM) utilize master data management methods that enable product teams in businesses to define, administer and publish this critical information to those who need it, including Sales. Our research shows that the use of dedicated PIM technology has helped almost half (47%) of organizations eliminate errors and mistakes and that 90 percent of those that use a single system gain competitive advantage through faster time to market. This year a significant transformation of where PIM and commerce software will converge further to help provide the information in the shape and form required even as it is required across smartphones and tablets. Our new Value Index on Product Information Management for 2014 will assess progress of vendors and their investments in products to help you determine which ones can best meet your needs.
Just as quality information is critical, so is the ability to use analytics to build metrics that can provide immediate visibility into the progress of sales. Depending on periodic reports and dashboards doesn’t work in the accelerated pace of business today. Mature organizations are using predictive analytics and data mining of big data repositories to extract previously inaccessible insights; this can be critical for large sales organizations that sell large volumes of products. We will assess the advances in sales analytics in a new benchmark to determine how they have facilitated change in sales operations and increased efficiency in their processes. We already found in 2013 through our benchmark research in location analytics are helping provide a competitive edge on the ability to sell effectively in a territory but also how they are designed and optimized to achieve specific quotas. A new generation of sales analytics are advancing and accessible through mobile technology. In addition our 2014 Value Index in Mobile Business Intelligence assessed 16 vendors of business intelligence tools on their ability to provide best in class accessibility through across smartphones and tablets.
These advances and others provide for sales organizations a variety of applications and tools that can be used by sales executives, management, operations managers and account representatives. Sales organizations also need improvement in other areas including learning and coaching, compensation and incentives, forecasting, setting objectives, activity tracking, recognition and rewards. In 2014 we will conduct new research on next-generation technologies such as social collaboration for coaching and improving skills and on mobile devices to track and assess sales efforts. Better use of coaching and playbooks can help everyone in sales find and apply best practices or the right sales assets to use in communicating with prospects. On another front, industry pundits and vendors are buzzing about gamification in motivating sales, this is nothing new, and there are practical ways of having contests and leader boards for the sales team or individual quotas.
Our new benchmark research coming out in 2014 examines the automation of compensation plans and incentives for sales. New tools make them readily accessible at any time to help sales reps and managers determine progress toward targets; these offer an automated way to escape the silos of spreadsheets and documents. We will also assess the state of vendors and products in the Value Index for Sales Compensation in 2014. In a related area it is also critical to optimize the effectiveness of sales quotas and align them to territory management, which can help maximize the potential of sales organizations. Also marketing and sales can align their efforts through use of demand generation to ensure the tracking of inbound and outbound marketing feeds into business processes through nurturing of dialogue and interactions. And in 2013 we saw significant improvement to integrate configuration, pricing and quote (CPQ) management into the deal process and the SFA aspects of opportunities.
I’ll say again that all of this change means we cannot depend on conventional wisdom that says you can just use SFA and personal productivity tools to understand and improve sales performance. Our research has found that impediments such as inconsistent execution (53%), scattered information (48%) and limited visibility (42%) are motivating technology investments. Analytics help to develop metrics for performance and planning, and the use of big data to mine and harvest information assets, can help. Moving to applications that automate interaction among sales teams can help achieve a common set of goals.
Our benchmark research in various aspects of sales continues to find significant opportunities for organizational improvement through better tools. Applications are easier to access and use from the cloud or on mobile technology. Dedicated software can help interconnect sales with the other lines of business. For example, a dedicated approach to sales and operations planning can help ensure that the forecast and planning process connects sales, operations and finance. In the area of talent management that my colleague covers that can enhance the range of key employees activities for sales including recruiting, onboarding to learning, performance and career planning, which can be done more effectively through collaboration between sales and HR. Many providers of sales applications are beginning to advance in this area to directly help sales be as efficient as possible.
Making sales people and processes more efficient and effective in using technology built for its particular purposes is critical to ensure the best outcomes. Sales will need to think beyond conventional wisdom and examine what is needed to be effective from sales management, manager and operations but also down to how help every account manager be as efficient as possible. Sales should also explore building alliances with finance and IT to see where faster investments can accelerate the potential to achieve the sales targets and revenue expectations of the organization. Use our sales-related research and assessments of applications and technology across vendors to learn where your opportunities may lie.
CEO & Chief Research Officer
January 27, 2014 in Big Data, Business Analytics, Business Collaboration, Business Intelligence (BI), Business Performance Management (BPM), Cloud Computing, Customer Performance Management (CPM), Financial Performance Management (FPM), Governance, Risk & Compliance (GRC), Information Applications (IA), Information Management (IM), Location Intelligence, Operational Intelligence, Operational Performance Management (OPM), Sales Performance Management (SPM), Social Media, Supply Chain Performance Management (SCPM), Workforce Performance Management (WPM) | Tags: Big Data, CIO, Information Optimization | by Mark Smith | Leave a comment
Businesses are always looking for ways to grow and to streamline their operations. These two goals can come into conflict because as organizations become larger it becomes more complicated to be agile and efficient. To help them understand and modify their processes, businesses can derive insights from analytics applied to their data. Today that data is available not only in the enterprise and cloud computing environments but also from the Internet. To collect, process and analyze it all is a challenge, one that an increasing number of organizations are meeting through the use of big data technologies. The resulting insights can help them make strategic business decisions such as where to focus efforts and how to engage with customers. At Ventana Research we have been working hard to understand the advancing technology that supports big data and its value through information optimization and bring clarity to the industry through our research and analysis of trends and products. There are many opinions about big data and fixation on the attributes of it through the V’s (volume, variety and velocity) and how to use it, often biased toward one technology or vendor; our research and analysis of the entire market cuts through the noise to provide not just facts but insights on best practices and methods to apply this technology to business problems.
There’s no doubt that big data can help organizations turn their information assets into insights that are critical for achieving growth and interacting more successfully with customers. It can help them access and integrate information for business use in ways that were not possible before. Among these new methods are simpler ways to access and consume information, including search based on natural language and cognitive computing, which is bringing forward advanced science to the processing of information. Big data also enables more effective visualization to support discovery and exploratory analytics. Machine data can be used to gain insights into the workings of technology that directly impacts the operations of the organization. We assert that big data drives operational efficiency through effective processing technology that expands the use of information though analytics and these innovative computing methods. The importance of these advances is shown in our recent benchmark research on information optimization, in which two-thirds (67%) of organizations said that improving operational efficiency is the leading reason to change how they make information available.
In 2013, large steps forward were made in big data technology. We saw the beginning of convergence among technological approaches as Hadoop, in-memory processing and data appliances intersect with specialized and traditional database systems. Users are learning how to gain value through insights from these technology investments. While we saw advances in visualization as shown in our predictive analytics research, using most of these tools requires advanced skills to ensure that the data is interpreted properly for facilitating actions, let alone decisions. Many organizations lack these skills in-house, our research shows.
Thus one challenge for 2014 is to acquire the competencies needed to get the best possible information from big data. Another is to improve processes for information optimization so that data, even about real-time events, can flow to business users and reduce the time it takes for them to use it effectively. New platforms and services can help make more types of information easier to understand and interact with. This is complemented by collaboration tools that can operate across mobile devices and get more information to more people wherever they are. We note also that unstructured data such as documents, images and text now is part of the information requirements for more than half of organizations that could use big data technology.
All of these tools and efforts towards information optimization can be useful as organizations try to improve the consistency and governance of their business-related information assets in key areas such as product information management and reduce duplication and conflicts in information about customers and employees along with focus on governance, risk and compliance (GRC). Failing to address these issues can lead to lost revenue, dissatisfied customers and decreased efficiency, all of which impact profitability. Our focus on product information management will continue as it is in high demand: We will release a new Value Index on the topic in 2014 to assess vendors and products and guide potential purchasers. There also have been advances in applications to help businesses manage information; for example, the use of master data management and data governance can help increase accuracy and outcomes from related business processes. In 2014 we will assess the current market for master data management as it impacts both business and IT through new benchmark research and continued coverage of technology developments. Because data no longer resides only in the enterprise, we will continue to track advances in using cloud computing for business applications and accessing and integrating the large amounts of data there. Cloud data is now a major factor in many organizations, and we will reassess the challenges with data in the cloud benchmark research to determine where investments and processes have progressed and where they still need to be improved.
Mainstream use of big data is leading organizations to invest in creating a new stream of information processes that can meet a variety of business needs. We have a whole line of new next-generation analytics research in the specific lines of business; the first are for finance, customer and human capital, and other areas planned for 2014 are in sales and marketing, which are still in the early adoption phase of big data but have generated significant interest about its potential.
Organizations have several options in the types of big data technology they choose. Some are using Hadoop and commercial versions of it from a variety of providers, others are using big data appliances, and still others are using in-memory computing and specialized databases. Our latest research finds that in 2014 more organizations plan to use Hadoop (24%), in-memory tools (23%) and appliances (15%) than will use an RDBMS (10%). This variety of technologies is generating new best practices in big data and how to use the resulting information. Big data is a critical innovative technology now important to 41 percent of organizations. Please consult my colleague Tony Cosentino’s research agenda in business analytics and big data, which outlines new methods to discover and explore big data effectively; he also has new research coming on big data analytics.
It is now possible for organizations to learn and apply best practices in using big data effectively across business and IT. Once that is accomplished users can examine how to make information flow easily into applications and optimize their use, too. At this point, however, many have yet to focus on integration of data and sources to ensure an efficient flow both in the enterprise and throughout cloud computing. This challenge we call big data integration, and we are conducting new research to identity the issues, methods and best practices here. Our research shows that for more than four out of five organizations that have 16 or more sources of data it is important to simplify access and use of it all and integration will help address this challenge. This year we will also have our annual Value Index on vendors and products in data integration and will expand to include the requirements for big data and cloud computing. The availability of technology for data integration is fueling new efforts in what I call integration optimization, which even includes handling of real-time event streams in complex event processing to produce operational intelligence. We have research on this and an upcoming Value Index. Use of this real-time information and analytics is helping organizations respond to issues more quickly than waiting for historical analysis to take place.
We expect significant advances in big data and information optimization in 2014. In this market, however, most organizations lack experience and skilled resources. We warn them not to investigate big data just because “everyone is doing it.” That is not necessarily true, so we recommend first reviewing the processes in your organization in which it can provide value, and then look at the architectural and technological approaches that best fit your needs and available resources.
CEO & Chief Research Officer