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Ventana Research recently released the results of our Next-Generation Business Planning benchmark research. Business planning encompasses all of the forward-looking activities in which companies routinely engage. The research examined 11 of the most common types of enterprise planning: capital, demand, marketing, project, sales and operations, strategic, supply chain and workforce planning, as well as sales forecasting and corporate and IT budgeting. We also aggregated the results to draw general conclusions.

Planning is the process of creating a detailed formulation of a program of action designed to achieve objectives. People and businesses plan to determine how to succeed in achieving those objectives. Planning also serves to structure the discussion about those objectives and the resources and tactics needed to achieve them. A well-managed planning process should be structured in that it sets measurable objectives and quantifies resources required to achieve them. Budgeting is a type of planning but somewhat different in that is financially focused and is done to impose controls that prevent a company from overspending and therefore failing financially. So while planning and budgeting are similar (and budgeting involves planning), they have different aims. Unlike budgeting, planning emphasizes the things that the various parts of the business focus on, such as units sold, sales calls made, the number and types of employees required or customers served.

Integrating the various business planning activities across a company benefits the senior leadership team, as I have written by enabling them to understand both the operational vr_NGBP_02_integrated_planning_works_betterand the financial consequences of their actions. There are multiple planning efforts under way at any time in a company. These plans typically are stand-alone efforts only indirectly linked to others. To be most effective, however, an individual business unit plan requires direct inputs from other planning efforts. A decade ago I coined the term “integrated business planning” to emphasize the need to use technology to better coordinate the multiple planning efforts of the individual parts of the company. There are good reasons to do this, one of which is accuracy. Our new research reveals that to be accurate, most (77%) planning processes depend to some degree on having access to accurate and timely data from other parts of the organization. For this reason, integrating the various planning processes produces business benefits: In our research two-thirds of companies in which plans are directly linked said that their planning process works well or very well. This compares favorably to 40 percent in those that copy planning data from individual plans to an integrated plan (such as the company budget) and just 25 percent of those that have little or no connection between plans.

Technology has been a major barrier preventing companies from integrating their planning efforts. Until relatively recently, joining the individual detailed plans of various departments and functions into an overall view was difficult because the available software, data and network capabilities were not sufficient to make it feasible and attractive to take this approach. To be sure, over the past decades there has been steady progress in making enterprise systems more accessible to ordinary users. But while dedicated planning software has become easier to use, evidently it’s still not easy enough. The research reveals that across the spectrum of corporate planning activities, three-fourths of organizations use spreadsheets to manage the process. We expect this to change over the next several years as the evolution in information technologies makes dedicated planning software a more compelling choice. One factor will be enhanced ease of use, which will be evident in at least two respects. Software vendors are recognizing that a better user experience can differentiate their product in a market where features and functions are a commodity. Ease of use also will extend to analytics and reporting, making it easier for business users to harness the power of advanced analytics and providing self-service reporting, including support for mobile devices. The other factor will be the ability to make the planning process far more interactive by utilizing in-memory processing to speed calculations. When even complex planning models with large data sets can be run in seconds or less, senior executives and managers will be able to quickly assess the impact of alternative courses of action in terms of their impact on key operating metrics, not just revenue and income. Having the means to engage in a structured conversation with direct reports will help executives be more effective in implementing strategy and managing their organization.

Technology is not the only barrier to better planning. The research demonstrates the importance of management in the process, correlating how well a planning process is managed with its accuracy. The large majority (80%) of companies that manage a planning process well or very well wind up with a plan that is accurate or very accurate. By contrast, just one-fourth of companies that do an adequate job achieve that degree of accuracy and almost none (5%) of those that do it poorly have accurate or very accurate results. Additionally, managing a planning process well requires clear communications. More than three-fourths (76%) of companies in which strategy and objectives related to plans are communicated very well have a process that works very well, while more than half (53%) with poor executive communication wind up with a planning process that performs poorly. And collaboration is essential to a well-functioning planning process. Most (85%) companies that collaborate effectively or very effectively said that their planning process is managed well, while just 11 percent of companies that collaborate only somewhat effectively expressed that opinion.

vr_ngbp_03_collaboration_is_important_for_planningCollaboration is essential because the process of planning in corporations ought to get everyone onto the same page to ensure that activities are coordinated. Companies have multiple objectives for their planning processes. Chief among these is accuracy. But since things don’t always go to plan, companies need to have agility in responding to changes in a timely and coordinated fashion. In a small business, planning can be informal because of the ease of communications between all members and the ease with which plans can be modified in response to changing conditions In larger organizations the planning process becomes increasingly difficult because communications become compartmentalized locally and diffused across the entire enterprise. Setting and to a greater degree changing the company’s course requires coordination to ensure that the actions of one part of the organization complement (or at least don’t impede) the actions of others. Coordination enables understanding of the impact of policies and actions in one part of the company on the rest. Yet only 14 percent of companies are able to accurately measure that impact, and fewer than half (47%) have even a general idea. Integrated business planning address that issue.

In most organizations budgeting and operational planning efforts are only loosely connected. In contrast, next-generation business planning closely integrates unit-level operational plans with financial planning. At the corporate level, it shifts the emphasis from financial budgeting to planning and to performance reviews that integrate operational and financial measures. It uses available information technology to help companies plan faster with less effort while achieving greater accuracy and agility.

For companies to improve competitiveness, their business planning must acquire four characteristics. First, planning must focus on performance, measuring results against both business and financial objectives. Second, it must help executives and managers quickly and intelligently assess all relevant contingencies and trade-offs to support their decisions. Third, it must enable each individual business planning group to work in one central system; this simplifies the integration of their plans into a single view of the company and makes it easy for planners in one part of the business to see what others are projecting. Fourth, it must be efficient in its use of people’s time. Success in business stems more from doing than planning. Efficient use of time enables agility, especially in larger organizations.

Today’s business planning doesn’t completely lack these features, but in practice it falls short – often considerably. Senior executives ought to demand more from the considerable amount of time their organization devotes to creating, reviewing and revising plans. They should have easy access to the full range of plans in their company. They must be able to engage in a structured dialog with direct reports about business plans, contingency plans and business unit performance. Information technology alone will not improve the effectiveness of business planning, but it can facilitate their efforts to realize more value from their planning.

Regards,

Robert Kugel – SVP Research


Data is an essential ingredient for every aspect of business, and those that use it well are likely to gain advantages over competitors that do not. Our benchmark research on information optimizationvr_Info_Optimization_02_drivers_for_deploying_information reveals a variety of drivers for deploying information, most commonly analytics, information access, decision-making, process improvements and customer experience and satisfaction. To accomplish any of these purposes requires that data be prepared through a sequence of steps: accessing, searching, aggregating, enriching, transforming and cleaning data from different sources to cre­ate a single uniform data set. To prepare data properly, businesses need flex­ible tools that enable them to en­rich the context of data drawn from multiple sources, collaborate on its preparation to serve business needs and govern the process of preparation to ensure security and consistency. Users of these tools range from analysts to operations professionals in the lines of business.

Data preparation efforts often encounter challenges created by the use of tools not designed for these tasks. Many of today’s analytics and business intelligence products do not provide enough flexibility, and data management tools for data integration are too complicated for analysts who need to interact ad hoc with data. Depending on IT staff to fill ad hoc requests takes far too long for the rapid pace of today’s business. Even worse, many organizations use spreadsheets because they are familiar and easy to work with. However, when it comes to data preparation, spreadsheets are awkward and time-consuming and require expertise to code them to perform these tasks. They also incur risks of errors in data and inconsistencies among disparate versions stored on individual desktops.

vr_Info_Optimization_16_information_software_evaluation_criteriaIn effect inadequate tools waste analysts’ time, which is a scarce re­source in many organizations, and can squander market opportunities through delays in preparation and unreliable data quality. Our information optimization research shows that most analysts spend the majority of their time not in actual analysis but in readying the data for analysis. More than 45 percent of their time goes to preparing data for an­al­y­sis or reviewing the quality and consistency of data.

Businesses need technology tools capable of handling data preparation tasks quick­ly and dependably so users can be sure of data quality and concen­trate on the value-adding as­pects of their jobs. More than a dozen such tools designed for these tasks are on the market. The best among them are easy for analysts to use, which our research shows is critical: More than half (58%) of participants said that usability is a very important evaluation criterion, more than any other, in software for optimizing information. These tools also deal with the large numbers and types of sources organizations have accumulated: 92 percent of those in our research have 16 to 20 data sources, and 80 percent have more than 20 sources. Complicating the issue further, these sources are not all inside the enterprise; they also are found on the Internet and in cloud-based environments where data may be in applications or in big data stores.

Organizations can’t make business use of their data until it is ready, so simplifying and enhancing the data preparation process can make it possible for analysts to begin analysis sooner and thus be more productive. Our analysis of time related to data preparation finds that when this is done right, significant amounts of time could be shifted to tasks that contribute to achieving business goals. We conclude that, assuming analysts spend 20 hours a week working on analytics, most are spending six hours on preparing data, another six hours on reviewing data for quality and consistency issues, three more hours on assembling information, another two hours waiting for data from IT and one hour presenting information for review; this leaves only two hours for performing the analysis itself.

Dedicated data preparation tools provide support for key tasks in areas that our research and experience finds that are done manually by about one-third of organizations. These data tasks include search, aggregation, reduction, lineage tracking, metrics definition and collaboration. If an organization is able to reduce the 14 hours previously mentioned in data-related tasks (that including preparing data, reviewing data and waiting for data from IT) by one-third, it will have an extra four hours a week for analysis – that’s 10 percent of a 40-hour work week. Multiply this time by the number of individual analysts and it becomes significant. Using the proper tools can enable such a reallocation of time to use the professional expertise of these employees.

This savings can apply in any line of business. For example,vr_NG_Finance_Analytics_10_data_issues_slow_delivery_of_metrics our research into next-generation finance analytics shows that more than two-thirds (68%) of finance organizations spend most of their analytics time on data-related tasks. Further analysis shows that only 36 percent of finance organizations that spend the most time on data-related tasks can produce metrics within a week, compared to more than half (56%) of those that spend more time on analytic tasks. This difference is important to finance organizations seeking to take a more active role in corporate decision-making.

vr_BDI_09_big_data_integration_starts_with_basicsAnother example is found in big data. The flood of business data has created even more challenges as the types of sources have expanded beyond just the RDBMS and data appliances; Hadoop, in-memory and NoSQL big data sources exist in at least 25 percent of organizations, according to our big data integration research. Our projections of growth based on what companies are planning indicates that Hadoop, in-memory and NoSQL sources will increase significantly. Each of these types must draw from systems from various providers, which have specific interfaces to access data let alone load it. Our research in big data finds similar results regarding data preparation: The tasks that consume the most time are reviewing data for quality and consistency (52%) and preparing data (46%). Without automating data preparation for accessing and streamlining the loading of data, big data can be an insurmountable task for companies seeking efficiency in their deployments.

A third example is in the critical area of customer analytics. Customer data is used across many departments but especially marketing, sales and customer service. Our research again finds similarvr_Info_Optimization_11_innovations_important_for_information issues regarding time lost to data preparation tasks. In our next-generation customer analytics benchmark research preparing data is the most time-consuming task (in 47% of organizations), followed closely by reviewing data (43%). The research also finds that data not being readily available is the most common point of dissatisfaction with customer analytics (in 63% of organizations). Our research finds other examples, too, in human resources, sales, manufacturing and the supply chain.

The good news is that these busi­ness-focused data preparation tools have usability in the form of spreadsheet-like interfaces and include analytic workflows that simplify and enhance data preparation. In searching for and profiling of data and examining fields based on analytics, use of color can help highlight patterns in the data. Capabilities for addressing duplicate and incorrect data about, for example, companies, addresses, products and locations are built in for simplicity of access and use. In addition data preparation is entering a new stage in which ma­chine learning and pat­tern recog­ni­tion, along with predictive analytics techniques, can help guide individuals to issues and focus their efforts on looking forward. Tools also are advancing in collaboration, helping teams of analysts work together to save time and take advantage of colleagues’ expertise and knowledge of the data, along with interfacing to IT and data management professionals. In our information optimization research collaboration is a critical technology innovation, according to more than half (51%) of organizations. They desire several collaborative capabilities ranging from discussion forms to knowledge sharing to requests on activity streams.

This data preparation technology provides support for ad hoc and other agile approaches to working with data that maps to how business actually operate. Taking a dedicated approach can help simplify and speed data preparation and add value by enabling users to perform analysis sooner and allocate more time to it. If you have not taken a look at how data preparation can improve analytics and operational processes, I recommend that you start now. Organizations are saving time and becoming more effective by focusing more on business value-adding tasks.

Regards,

Mark Smith

CEO and Chief Research Officer

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