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Using our research, best practices and expertise, we help you understand how to optimize your business processes using applications, information and technology. We provide advisory, education, and assessment services to rapidly identify and prioritize areas for improvement and perform vendor selection
We provide guidance using our market research and expertise to significantly improve your marketing, sales and product efforts. We offer a portfolio of advisory, research, thought leadership and digital education services to help optimize market strategy, planning and execution.
Services for Technology Vendors
We provide guidance using our market research and expertise to significantly improve your marketing, sales and product efforts. We offer a portfolio of advisory, research, thought leadership and digital education services to help optimize market strategy, planning and execution.
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How we can help
Consulting
Consulting where we deliver expert guidance with our experience, expertise and market research through workshops and assessments for better business outcomes.
Advisory
Advisory through our proactive and informed expert advice and insights for optimization of decisions through our Ventana On-Demand service designed for value every month of the year.
Research
Research enables insights from our industry analyst team and market research with our Benchmark Research, Dynamic Insights and Value Index research products that provide facts for decisions.
Education
Education in a range of business, technology and vertical industry topics through our publishing of digital content in mediums and styles for impactful insights across an entire organization.
Some of our Latest Research
Generative Automation: An Alternative for Process Optimization
Analyst Perspective
Agents are all the rage—and for a good reason. They are a way to automate work almost effortlessly so that repetitive and boring tasks get done with the least amount of effort on the part of the operator. In business, agents can be a boon for customer satisfaction and a way to improve worker productivity. They are alluring, with an almost unlimited number of potential use cases.
Technology Transforms ERP for a More Effective Finance Department
Analyst Perspective
ERP systems have been the central nervous system of enterprises for more than three decades, handling business-critical process management and recordkeeping. While their basic outlines are unchanged, today’s systems are far more capable in their functional depth, adaptability, usability and manageability. Especially for cloud-based systems, they are far easier to maintain. Decades of refinement and focused development to support specific industries, and even specialized categories within these industries, have increased their utility while decreasing the total cost of ownership, especially in implementation expense and maintenance. Artificial intelligence (AI) is the latest supporting technology to increase the business value of the software. So, when considering replacing existing ERP software, it’s most important to understand and evaluate how a new system can add to the capabilities of the incumbent and how to manage the organizational change that will become possible and necessary with that change.
Gain Finance Department Productivity with Straight-Through Processing
Analyst Perspective
Improving data management is at the forefront of my Office of Finance research practice because, when not managed well, it can have a profoundly negative impact on departmental efficiency, individual performance, organizational agility and sustainability. Conversely, straight-through processing (STP), a business process design and data management methodology, reduces process friction throughout an organization and, by minimizing errors, builds trust in the accuracy and reliability of all data, including that used in analysis, accounting, billing and performance management.
Competitive Innovation is Improving the Economics of GenAI
Analyst Perspective
At this stage of the development of Generative AI, there’s much we can see clearly (at least we think we can), but there’s even more likely to surprise us. As that great 20th-century philosopher and hall-of-fame catcher, Yogi Berra, famously said, “It’s tough to make predictions, especially about the future.” The breadth and speed of innovation today in all aspects of GenAI rivals that of the internet in the 1990s, and for the same reason.
Oracle Demonstrates Embedded AI for Productivity Gains
Analyst Perspective
Oracle held an industry analyst summit recently where the focus was on artificial intelligence (AI) and embedded AI. At the event, Oracle demonstrated progress in adding useful AI-enabled capabilities to its business applications, especially in finance and accounting, supply chain, HR and revenue management. To put this into context, across the software industry, AI is already at work in many finance-focused applications that are currently available, albeit often in limited release. We are in the early stages of a new generation of business applications. After decades of limited innovation, software providers are in a race to add AI capabilities to their software as fully and rapidly as possible without frustrating users, while retaining a reputation for reliability and security. I recently wrote about the ability of AI and generative AI (GenAI) to boost productivity and the need for guardrails and risk management in applying this technology. Buyers and users of business applications should expect a steady stream of announcements from software providers for the foreseeable future.
The CFO AI Trilemma: Cut Costs, Accomplish More or Both
Analyst Perspective
We’re quickly approaching the moment when it becomes clear that artificial intelligence (AI) and generative AI (GenAI) will not be free. As that happens, we will discover who’s willing to pay how much and for what. After nearly 18 months of unlimited use-case fantasizing, it should be obvious that not all the potential applications of AI can be realized over the next three to five years because they fail a cost/benefit test. In theory, AI’s potential is almost limitless, but so far, little thought has been paid to how the economics will play out. The issue of AI costs is important because even uses that are technically feasible will be passed over if buyers find them more costly than they are worth. Business software providers, especially those serving the technology-hesitant office of finance, will need to correctly anticipate the market willing to pay for AI when making their investments. Software buyers will need to consider the current and future ability of a software provider to offer reliable AI-infused capabilities that address their requirements at a price they’re willing to pay. Cost/benefit analyses will have a strong influence on how businesses structure their strategic and tactical approaches to AI and therefore how demand for AI — especially AI for business purposes — is likely to play out in the market.
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