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Unit4 is a global business software vendor focused on business and professional services, the public sector and higher education. Recently company executives met with industry analysts to provide an update of its strategic roadmap and to recap its accomplishments since being acquired by a private equity firm in 2014. Unit4 is the result of successive mergers of ERP and business software companies, notably CODA and Agresso. The company is also a part-owner (with salesforce.com and others) of independently run FinancialForce, which sells a cloud-based ERP system built on the Force.com platform.

All vendors of business applications – especially ERP – are challenged today by a more disruptive technology environment than they have faced over the past 15 years. Unit4 is in the beginning phases of a planned evolution of its product and go-to-market strategy designed to gain share in the global ERP market. Parts of what it presented to analysts are already in place while other parts lie ahead still on its multiyear roadmap.

From a technology standpoint, the ERP software market has been in period of relative stasis since the Y2K bubble burst in 2000. Other than the arrival of cloud-based software as a service, the pace of innovation in this category has been relatively slow, especially relative to the pace set in the 1990s. Now this market is in the process of changing and organizations are deciding when to replace their ERP as I have written. The accumulation of more than a decade of small but steady incremental technology advances is giving vendors new possibilities for designing their applications. For its part Unit4 has been evolving the architecture underlying its applications to make them easier to implement (the company calls it “an elastic foundation”). It is also using Microsoft’s Azure platform to enable it to offer, for example, predictive and prescriptive analytics, mobile application functionality and intelligent process automation.

Unit4’s product and marketing strategy aims to seize opportunities provided by technology disruptions to gain share in a consolidating market.  We see three main sources of technology disruption that increasingly will be driving buyer preferences in the ERP market over the next decade.

One is the use of technologies to provide new more valuable capabilities. Here are some examples.

User efficiency is increased by greater automation of repetitive tasks (especially in finance and accounting departments). In addition, many legacy ERP systems have gaps in their architecture or their design that require manual process steps, process interventions (that require input rather than requiring it by exception) and manual data transfers. Another aspect of automation is reducing the need for data entry. For instance, an individual’s appointments booked in Microsoft Outlook can be reused for billing. Some of the built-in automation will be designed for vertical industries to reflect their specific requirements.

Overall effectiveness can be enhanced by use of more advanced predictive and prescriptive analytics as an integral part of a transaction-processing application such as ERP. These techniques can improve the quality of decisions that individuals make in executing transactions. Unit4’s strategy is to create vertical-specific advanced analytics to address the needs of these businesses. Effectiveness also can be improved by embedding in-context collaboration capabilities, which I have written about. That is, such software is “aware” of what an individualvr_bti_br_technology_innovation_priorities is doing and, for example, provides ready access to the specific colleagues that the user may need to contact at that moment and enables them to share all underlying data and documents that might be relevant under the specific circumstances (such as a master contract or previous instant messages). Our benchmark research on business technology innovation shows that collaboration ranks second in importance behind analytics as a technology innovation priority. Collaborative capabilities in software will multiply over the next several years as software transitions from the rigid constructs established in the client/server days, which force users to adapt to the limitations of the software, to fluid and dynamic designs that mold themselves around the needs of  users. Business is an inherently collaborative process anyway, so such capabilities are important to the productivity of business software users.

The user experience is improved by rethinking its design and organization of the screens. Unit4 aims to improve the mental ergonomics of working with its applications. The redesign reduces screen clutter, facilitates navigation across screens to complete a task and enhances graphics to make interactions more pleasing and efficient.

vr_Office_of_Finance_01_ERP_replacementUnit4 encapsulates these existing and prospective improvements in the slogan “self-driving ERP.” One element of this metaphor is reducing the amount of effort and attention required of individuals to handle mundane repetitive chores. The other is that by using built-in analytics that can spot potential issues and opportunities in the data, individuals will be able to spot and take action on situations that have the highest payoff. The company hopes to extend the capabilities of its ERP software beyond a simple transaction processing engine to include differentiated capabilities to run businesses more -intelligently.

In addition to providing scope for product differentiation, offering organizations far more than a like-for-like replacement of their existing software may provide an incentive to replace existing software sooner. One impact of the slow evolution of technology on the ERP market is that, as shown in our Office of Finance research, on average, companies are holding on to their ERP software a year longer than they did a decade ago.

A second technology that is already disrupting the market is the increasing adoption of cloud-based or hybrid-cloud-based ERP systems by Unit 4’s key target buyers: larger midsize companies in business and professional services, government and higher education. These sorts of organizations tend to have less capable IT staffs and smaller IT budgets than large public companies. This affects the performance of their systems because the software and hardware are not always kept up to date. For these buyers, a cloud-based product can deliver better performance than they currently have at a lower total cost of ownership.

The third disruptive technology approach is permitting end users to configure the ERP application without having to modify its code. Cloud-based applications that are designed to be used in a multitenant environment must be flexible enough to appeal to the widest possible audience. This requires an architecture that enables individual organizations to readily configure processes and make adjustments without altering the underlying code. It also means having industry-specific or even micro-vertical capabilities built into the system. Vendors that want to offer their software in a multitenant environment have to do this, but it is useful even in an on-premises or private cloud deployment because it can reduce the effort and expense of deploying the software. Properly executed, this approach makes the software more adaptable to how a company does business, rather than forcing an organization either to live with the software as is or pay significant fees to modify it to meet specific requirements. Unit4 was already heading in this direction before the change in ownership and management.

The management team also has been tackling internal issues and revamping its go-to-market strategy, essentially completing the integration of the various software companies. The company will invest in promoting a single master brand for visibility.  Product naming has been simplified to “Unit4” plus a functional label construction (such as “Financials,” “Professional Services” and “Consolidation”). This will apply across the board except for “Business World,” which has good recognition on its own. Some once local or regional products such as Travel and Entertainment are now available worldwide. Unit4 is increasing its exposure in North America, increasing its sales coverage where it has had a limited presence, as well as focusing its European sales efforts in the U.K., France and Germany.

Technology and innovative software design will drive consolidation of the ERP market over the coming decade. Unit4’s  management team has made necessary changes to its sales and marketing management. Its strategies are sound and essential to its long-term success in this market environment. Combined they reflect a formula that successful business applications vendors will use to gain advantage in the newly dynamic ERP market. The company is well-positioned to achieve its objectives from product and market standpoints. At the least, Unit4 has the potential to grow faster in its fragmented markets by taking share from smaller vendors that do not have the critical mass to make the necessary investments in products, sales and marketing. (By analogy, this is similar to what happened with a long list of DOS business applications that did not have a recurring maintenance revenue stream to fund redevelopment on Windows.). However, its strategies are not unique. For that reason (and I hate to state the obvious), Unit4’s management will need to execute its strategy well. To ensure that it gains sufficient market share to sustain a competitive position, it will need to innovate faster than its competitors in shorter product cycles and execute in the field consistently.

Regards,

Robert Kugel – SVP Research

IBM’s Vision user conference brings together customers who use its software for financial and sales performance management (FPM and SPM, respectively) as well as governance, risk management and compliance (GRC). Analytics is a technology that can enhance each of these activities. The recent conference and many of its sessions highlighted IBM’s growing emphasis on making more sophisticated analytics easier to use by – and therefore more useful to – general business users and their organizations. The shift is important because the IT industry has spent a quarter of a century trying to make enterprise reporting (that is, descriptive analytics) suitable for an average individual to use with limited training. Today the market for reporting, dashboards and performance management software is saturated and largely a commodity, so the software industry – and IBM in particular – is turning its attention to the next frontier: predictive and prescriptive analytics. Prescriptive analytics holds particular promise for IBM’s analytics portfolio.

The three basic types of analytics – descriptive, predictive and vr_NG_Finance_Analytics_09_too_much_time_to_prepare_dataprescriptive – often are portrayed as a hierarchy, with descriptive analytics at the bottom and predictive and prescriptive (often referred to as “advanced analytics”) on the next two rungs. Descriptive analytics is like a rear-view mirror on an organization’s performance. This category includes variance and ratio analyses, dashboards and scorecards, among others. Continual refinement has enabled the software industry to largely succeed in making descriptive analytics an easy-to-use mainstream product (even though desktop spreadsheets remain the tool of choice). Today, companies in general and finance departments in particular handle basic analyses well, although they are not as effective as they could be. Our research on next-generation finance analytics shows, for example, that most financial analysts (68%) spend the largest amount of their time in the data preparation phases while a relatively small percentage (28%) use the bulk of their time to do what they are supposed to be doing: analysis. We find that this problem is mainly the result of issues with data, process and training.

The upward shift in focus to the next levels of business analytics was a common theme throughout the Vision conference. This emphasis reflects a key element of IBM’s product strategy: to achieve a competitive advantage by making it easy for most individuals to use advanced analytics with limited training and without an advanced degree in statistics or a related discipline.

The objective in using predictive analytics is to improve an organization’s ability to determine what’s likely to happen under certain circumstances with greater accuracy. It is used for four main functions:

  • Forecasting – enabling more nuanced projections by using multiple factors (such as weather and movable holidays for retail sales)
  • Alerting – when results differ materially from forecast values
  • Simulation – understanding the range of possible outcomesvr_NGBP_08_predictive_analytics_underused_in_planning under different circumstances
  • Modeling – understanding the range of impacts of a single factor.

Our research on next-generation business planning finds that despite its potential to improve the business value of planning,  only one in five companies use predictive analytics extensively in their planning processes.

Predictive analytics can be useful for every facet of a business and especially for finance, sales and risk management. It can help these functions achieve greater accuracy in sales or operational plans, financial budgets and forecasts. The process of using it can identify the most important drivers of outcomes from historical data, which can support more effective modeling. Because plans and forecasts are rarely 100 percent accurate, a predictive model can support timely alerts when outcomes are significantly different from what was projected, enabling organizations to better understand the reasons for a disparity and to react to issues or opportunities sooner. When used for simulations, predictive models can give executives and managers deeper understanding of the range of potential outcomes and their most important drivers.

Prescriptive analytics, the highest level, help guide decision-makers to make the best choice to achieve strategic or tactical objectives under a specified set of circumstances. The term is most widely applied to two areas:

  • Optimization – determining the best choice by taking into account the often conflicting business objectives or other forms of trade-offs while factoring in business constraints – for example, determining the best price to offer customers based on their characteristics. This helps businesses achieve the best balance of potential revenue and profitability or farmers to find the least costly mix of animal feeds to achieve weight objectives.
  • Stochastic Optimization – determining the best option as above but with random variables such as a commodity price, an interest rate or sales uplift. Financial institutions often use this form of prescriptive analytics to understand how to structure fixed income portfolios to achieve an optimal trade-off between return and risk.

General purpose software packages for predictive and prescriptive analytics have existed for decades, but they were designed for expert users, not the trained rank-and-file. However, some applications that employ optimization for a specific purpose have been developed for nonexpert business users. For example, price and revenue optimization software, which I have written about is used in multiple industries.  Over the past few years, IBM has been making progress in improving ease of use of general purpose predictive and prescriptive analytics. These improvements were on display at Vision. One of the company’s major initiatives in this area is Watson Analytics. It is designed to simplify the process of gathering a set of data, exploring it for meaning and importance and generating graphics and storyboards to convey the discoveries. Along the way, the system can evaluate the overall suitability of the data the user has assembled for creating useful analyses and assisting general business users in exploring its meaning. IBM offers a free version that individuals can use on relatively small data sets as a test drive. Watson is a cognitive analytics system, which means it is by nature a work in progress. Through experience and feedback it learns various things including terminologies, analytical methods and the nuances of data structures. As such it will become more powerful as more people use it for a wider range of uses because of the system’s ability to “learn” rather than rely on a specific set of rules and logic.

Broader use of optimization is the next frontier for business software vendors. Created and used appropriately, optimization models can deliver deep insights into the best available options and strategies more easily, accurately, consistently and effectively than conventional alternatives. Optimization eliminates individual biases, flawed conventional wisdom and the need to run ongoing iterations to arrive at the seemingly best solution. Optimization is at the heart of a network management and price and revenue optimization, to name two common application categories. Dozens of optimization applications (including ILOG, which IBM acquired) are available, but they are aimed at expert users.

IBM’s objective is to make such prescriptive analytics useful to a wider audience. It plans to infuse optimization capabilities it into all of its analytical applications. Optimization can be used on a scale from large to small. Large-scale optimization supports strategic breakthroughs or major shifts in business models. Yet there also are many more ways that the use of optimization techniques embedded in a business application – micro-optimization – can be applied to business. In sales, for example, it can be applied to territory assignments taking into account multiple factors. In addition to making a fair distribution of total revenue potential, it can factor in other characteristics such as the size or profitability of the accounts, a maximum or minimum number of buying units and travel requirements for the sales representative. For operations, optimization can juggle maintenance downtime schedules. It can be applied to long-range planning to allocate R&D investments or capital outlays. In strategic finance it can be used to determine an optimal capital structure where future interest rates, tax rates and the cost of equity capital are uncertain.

Along the way IBM also is trying to make optimization more accessible to expert users. Not every company or department needs or can afford a full suite of software and hardware to create applications that employ optimization. For them, IBM recently announced Decision Optimization on Cloud (DOcloud), which provides this capability as a cloud-based service; it also broadens the usability of IBM ILOG CPLEX Optimizer. This service can be especially useful to operations research professionals and other expert users. Developers can create custom applications that embed optimization to prescribe the best solution without having to install any software. They can use it to create and compare multiple plans and understand the impacts of various trade-offs between plans. The DOcloud service also provides data analysis and visualization, scenario management and collaborative planning capabilities. One example given by IBM is a hospital that uses it to manage its operating room (OR) scheduling. ORs are capital-intensive facilities with high opportunity costs; that is, they handle procedures that utilize specific individuals and different combinations of classes of specialists. Procedures also have different degrees of time flexibility. Without using an optimization engine to take account of all the variables and constraints, crafting a schedule is time-consuming. And since “optimal” solutions to business problems are fleeting, an embedded optimization engine enables an organization to replan and reschedule quickly to speed up decision cycles.

Businesses are on the threshold of a new era in their use of analytics for planning and decision support. However, numerous barriers still exist that will slow widespread adoption of more effective business practices that take full advantage of the potential that technology offers. Data issues and a lack of awareness of the potential to use more advanced analytics are two important ones. Companies that want to lead in the use of advanced analytics need leadership that focuses on exploiting technology to achieve a competitive advantage.

Regards,

Robert Kugel – SVP Research

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