Robert Kugel's Analyst Perspectives

We live in a time of uncertainty, not unpredictability. Managing an organization in uncertain times is always hard, but tools are available to improve the odds for success by making it easier and faster to plan for contingencies and scenarios. Software makes it possible to quickly consider the impact of a range of events or assumptions and devise a set of plans to deal with them. Dedicated planning and budgeting software has been around for decades but is about to become all the more useful as vendors increasingly incorporate artificial intelligence using machine learning to assist in scenario planning. Organizations can quickly investigate the impact of different contingencies and the consequences of a range of reactions to them.

Topics: Office of Finance, Data Management, Business Planning, AI and Machine Learning, digital finance

Ventana Research uses the term “data pantry” to describe a method of data storage (and the technology and process blueprint for its construction) created for a specific set of users and use cases in business-focused software. It’s a pantry because all the data one needs is readily available and easily accessible, with labels that are immediately recognized and understood by the users of the application. In tech speak, this means the semantic layer is optimized for the intended audience. It is stocked with data gathered from multiple sources and immediately available for analysis, forecasting, planning and reporting. This does away with the need for analysts to repeatedly perform data extraction, enrichment or transformation motions from the required source systems, all but eliminating the substantial amount of time analysts and business users routinely spend on data preparation.

Topics: Continuous Planning, Business Intelligence, Data Management, Business Planning, Data, Financial Performance Management, Enterprise Resource Planning, AI and Machine Learning, continuous supply chain, data operations, digital finance, profitability management, Analytics & Data, Streaming Data & Events

A predictive finance department is one that can command technology to be more forward-looking and action-oriented while still fulfilling its core role of handling the financial elements of its organization including accounting, treasury and corporate finance. Beyond just automating rote tasks, technology also facilitates a shift toward becoming a predictive finance organization. Greater amounts of information, now available in near real time, and the increasing use of artificial intelligence (AI), enable more immediate analyses and assessments of possible courses of action, providing executives and managers the ability to better anticipate change and the agility to adapt quickly to unexpected circumstances.

Topics: Office of Finance, business intelligence, Data Management, Business Planning, Financial Performance Management, ERP and Continuous Accounting, AI and Machine Learning, digital finance

A few years ago – somewhat tongue in cheek – I began using the term “data pantry” to describe a type of data store that’s part of a business application platform, created for a specific set of users and use cases. It’s a data pantry because, unlike a general-purpose data store such as a data warehouse, everything the user needs is readily available and easily accessible, with labels that are immediately recognized and understood.

Topics: Data Management, Business Planning, Financial Performance Management, ERP and Continuous Accounting, AI and Machine Learning, digital finance

The use of artificial intelligence (AI) using machine learning (ML) will be the single most important trend in business software this decade because it can multiply the investment value of such applications and provide vendors an important source of differentiation to achieve a competitive advantage in what are today very mature software categories. I assert that by 2025, almost all Office of Finance software vendors will have incorporated some AI capabilities to reduce workloads and improve performance. However, software vendors will be challenged to apply innovations in this area quickly while ensuring that the AI capabilities function well enough in the real world to foster rapid adoption while avoiding user frustration. The failures of the Apple Newton and Microsoft’s Clippy office assistant stand out as examples of too-ambitious-too-soon attempts at infusing intelligent automation.

Topics: Office of Finance, embedded analytics, Data Management, Business Planning, Financial Performance Management, ERP and Continuous Accounting, AI and Machine Learning, digital finance

The use of blockchain distributed ledgers in business processes is now a common theme in many business software vendors’ presentations. The technology has a multitude of potential uses. However, presentations about the opportunities for digital transformation always leave me wondering: How is this magic going to happen? I wonder this because the details about how data flows from point A to point B via a blockchain are critically important to blockchain utility and therefore the pace of its adoption.

Topics: Planning, Predictive Analytics, Forecast, FP&A, Machine Learning, Reporting, budget, Budgeting, Continuous Planning, Analytics, Data Management, Cognitive Computing, Integrated Business Planning, AI, forecasting, consolidating

Ventana Research uses the term “predictive finance” to describe a forward-looking, action-oriented finance organization that places emphasis on advising its company rather than fulfilling the traditional roles of a transactions processor and reporter. Technology is driving the shift away from the traditional bean-counting role. The cumulative evolution of software advances will substantially reduce finance and accounting workloads by automating most of the mechanical, rote functions in accounting, data preparation and reporting. (I recently summarized these in a “Robotic Finance”)

Topics: Planning, Predictive Analytics, Forecast, FP&A, Machine Learning, Reporting, budget, Budgeting, Continuous Planning, Analytics, Data Management, Cognitive Computing, Integrated Business Planning, AI, forecasting, consolidating

When applying information technology to drive better business performance, companies and the systems integrators that assist them often underestimate the importance of organizing data management around processes. For example, companies that do not execute their quote-to-cash cycle as an end-to-end process often experience a related set of issues in their sales, marketing, operations, accounting and finance functions that stem from entering the same data into multiple systems. The inability to automate passing of data from one functional group to the next forces people to spend time re-entering data and leads to fragmented and disconnected data stores. The absence of a single authoritative data source also creates conflicts about whose numbers are “right.” Even when the actual figures recorded are identical, discrepancies can crop up because of issues in synchronization and data definition. Lacking an authoritative source, organizations may need to check for and resolve errors and inconsistencies between systems to ensure, for example, that what customers purchased was what they received and were billed for. The negative impact of this lack of automation is multiplied when transactions are complex or involve contracts for recurring services.

Topics: Big Data, Mobile, ERP, Office of Finance, Operational Performance Management (OPM), Operations, Management, close, closing, computing, end-to-end, Analytics, Cloud Computing, Data Management, Business Performance Management (BPM), CRM, Data, finance, Information Applications (IA), Information Management (IM), Sales Performance Management (SPM), Supply Chain Performance Management (SCPM), FPM

One of the potential benefits of cloud computing to access business applications and data is its potential to improve the situational awareness of executives and managers. By this I mean their understanding of what’s going on outside their company in addition to what’s happening within it. Today people have access to a trove of information about their own company, which is the result of decades of investment in an expanding range of enterprise transaction systems (ERP, CRM and supply chain management, for example) and convenient data stores that make accessing data easier than ever. But although people have access to internal information, most have big gaps in their knowledge about what’s going on in the outside world. Take, for example, market trends, information about a competitor’s, supplier’s or customer’s financials or industry-specific demand forecasts. Our benchmark research shows that while two-thirds of companies are satisfied with their ability to integrate information from standard internal sources, only 39 percent feel that way about reference or competitive data from external sources and 36 percent about text data from social media.

Topics: Operational Performance Management (OPM), Cloud Computing, Data Integration, Data Management, Business Performance Management (BPM), Customer Performance Management (CPM), Data, finance, Financial Performance Management (FPM), Information Management (IM), Sales Performance Management (SPM), Supply Chain Performance Management (SCPM), Workforce Performance Management (WPM), FPM

Informatica and Exterro have announced a partnership in the market for discovery of electronic data and documents (known as e-discovery). Exterro has made its reputation in e-discovery workflow and legal holds management while Informatica is a leader in data integration that our Value Index finds as the top and Hot rated provider. The partnership is designed to provide users of Exterro’s Fusion E-Discovery software with a single point of control for organizing and managing legal and preservation holds (that is, preventing electronic data from alteration or deletion) of unstructured and structured data that are held in Informatica’s Data Archive. Informatica specializes in the efficient management of information assets, which our benchmark research shows is not easy for most organizations to do because they have data spread across multiple applications and systems: Two-thirds of organizations said that this makes it difficult to manage information. By consolidating in a single repository the storage of information that is likely to be the subject of discovery, companies can simplify and cut the cost of the search process as well as reduce risk. Orchestrating legal and preservation holds can be complex since multiple people or groups within a company may be legally involved with the same data over an extended period of time. Moreover, it’s important to ensure that once the holds are no longer needed, all data that can be eliminated is eliminated.

Topics: Office of Finance, Operational Performance Management (OPM), eDiscovery, Exterro, Data Governance, Data Management, Governance, Risk & Compliance (GRC), Informatica, Business Performance Management (BPM), compliance, Data, Financial Performance Management (FPM), Information, Information Applications (IA), Information Management (IM), Risk, Sales Performance Management (SPM), Workforce Performance Management (WPM)