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Making Tactical Practical with Role-Based Analytics

In today’s competitive environment, companies must rapidly adapt to changing business conditions by adjusting strategy. Such course adjustments generate a wave of response throughout the organization. An edict from the CEO to boost fiscal year profits, for example, can create a scurried search for reports and spreadsheets as business groups search for data to help fulfill their roles in the new strategy. And when the appropriate reports don’t exist, IT teams are called in to create them by sifting through data and building the required calculations.

 

Role-based analytics offer an alternative to the chaos that can ensue when companies seek a rapid change in course. While today’s organizations are data rich, this data is often not available in a way that is useful for various business functions. By collecting and analyzing data based on modeling and algorithms specific to business roles, role-based analytics software helps companies capitalize on existing data and empower employees to make faster, more effective decisions. This effective use of data is a critical component of creating competitive advantage.

 

Understanding Role-Based Analytics

 

In seeking a competitive edge, many forward-thinking companies have implemented performance management (PM) applications as a way to more easily measure and monitor their businesses with data from existing systems. To streamline processes and facilitate better decisions with this data, PM offers a high-level capability for linking strategy with operations, budgeting, forecasting, planning, and financial and regulatory reporting.

 

Role-based analytics takes such analysis a step further, making it easy for employees at all levels within a company to make better decisions and improve their specific processes. The pre-built models and algorithms used in role-based analytics integrate, format and deliver the appropriate data from enterprise systems based on the end user’s functional role. Whether an executive or an accountant, a sales manager or a production specialist, the end user spends less time gathering data and more time analyzing the critical key performance indicators (KPIs) built into the solution.

 

Because role-based analytics aggregate data into a central server-based location, personnel work from the same data source, ensuring consistent analysis throughout the organization as opposed to duplicated efforts that muddy the performance picture and inhibit quick decisions. The analysis is then delivered in a form specified by the end user, such as a dashboard, scorecard, gauge or Web report.

 

For example, while some functional groups may prefer analyzed data in the form of a Web report, a group like accounting might be more comfortable with a spreadsheet format. Management and executives often prefer dashboards because they provide a high-level view of KPIs like sales and expenses.

 

While most companies are on a level playing field when it comes to the amount of available data, corporate culture and business process sophistication varies enough to wipe out this equality. Some organizations approach decision-making on gut instinct, while others base it on sometimes chaotic spreadsheet views and still others actually perform detailed, albeit time-consuming, analyses. No matter how sophisticated the company’s business processes were previously, role-based analytics offer a fast, reliable way of enforcing consistent metrics and definitions throughout the organization to create a clear picture of performance.

 

Role-Based Analytics across the Company

 

Changes to business strategy often start with a simple email from the CEO. However, without the right technology, a seemingly straightforward mandate can create a scramble to monitor critical KPIs, slowing down strategic progress.

 

In a role-based analytics environment, each department is armed with accessible role-based data that can allow them to react quickly to a mandate for increasing fiscal year profits, for example, without getting mired in extraneous details. Each organization is equipped with tools for managing and tracking its effectiveness in this strategy.

 

Executives. Role-based analytics algorithms are prebuilt to measure and monitor exactly what correlates with executive-level strategy. Role-based analytics offer the ability to set thresholds that generate alarms if a KPI, like profitability, exceeds or falls below specified limits. Using dashboards, executives and managers can click on the KPI in question and drill down to locate the problem, in transactional detail if necessary, while the department where the issue originated may already be taking corrective action due to the real-time aspect of the analytics.

 

Accounting and finance. Many times, it is assumed that accounting and finance simply provides numbers, but there is actually a great deal this group can do with the proper analytical tool to identify which functional departments need to more closely evaluate profitability.

 

For example, using role-based analytics to study the general ledger helps this group quickly determine income by various legal entities, as well as how the different company profit centers rank and which cost centers have the highest expenses. Uncovering problem areas allows companies to take timely corrective action for improving profits.

 

Also, role-based analytics lets finance more efficiently manage cash flow with thorough evaluation of accounts payable and accounts receivable. Metrics, budgets, assets and financial ratios are readily available for assessment.

 

Sales. A sales department has specific business questions about its performance, such as how sales are progressing by region, product and customer. Many times, basic reports provide data without providing the calculations to access these metrics, which are built in to the algorithms. Role-based analytics also provides information about shipping and overall performance of the sales organization.

 

Procurement and supplier relationship management. Role-based analytics allows a procurement department to assess its overall effectiveness with easy access to information, such as the amount of purchase orders processed, the number of transactions at various stages in the procurement cycle, and the number and volume of contracts. From an organizational standpoint, information on processing times relative to specific buying groups helps procurement identify opportunities to buy in bulk and reduce order lead-time across commodities, which helps the company maximize its bottom line.

 

These efficiencies created by role-based analytics help procurement better manage suppliers. For example, vendors are ranked by volume and revenue, allowing procurement to better leverage spending for volume discounts. In addition, vendor performance indicators like on-time delivery are tracked so that there are no negative impacts on company performance.

Production. Using role-based analytics, production departments can track performance at the factory level and identify the efficiency of plants in making certain products. This information could impact the choice to move production lines around as a way to improve facility performance and profitability.

 

With most production facilities running three shifts per day, seven days a week, companies without labor analysis are sometimes unaware that they are incurring excess labor hours or overtime. Role-based analytics help decrease labor costs by providing information to accurately forecast labor requirements at various locations.

 

Where a product is in the cycle determines when a company can recognize revenue, so time to delivery is another KPI for production departments. With role-based analytics, a company may find that it must reevaluate shipping partners because it is incurring costs due to delivery delays. In addition, analytics calculates the relationship between the number of shipments processed and the resulting revenue.

 

Role-based analytics also offers a window to work order materials usage and cost, as well as data on product quality and yield.

 

Inventory. Role-based analytics provides the ability to tightly control inventory by consolidating information on turns, returns and material movement through the production process. Details such as the number of inventory days in each warehouse ensure that inventory is optimized for profitability and adequate supply. Role-based analytics also provides a stock overview and valuation, as well as inventory forecasts.

 

Whether a company tracks physical inventory by hand or scanner, role-based analytics provide information on inventory accuracy to minimize impact on the production process. Details on inventory demand are also available, and shortages and overages are quickly identified in order to isolate and correct problems that could impact profitability or customer retention.

 

Asset management. Unplanned maintenance of key equipment can wreak havoc with a company’s bottom line by slowing or halting production and other key processes. Role-based analytics includes asset analysis that provides information on maintenance costs, work orders and warranty claims so that a company can better decide when it is time to refurbish or replace equipment.

 

Customer relationship management (CRM). To keep customers happy in today’s competitive marketplace, role-based analytics tracks the efficiency of services impacting the customer by aggregating information on call center and field service effectiveness, as well as other CRM processes.

 

Implications for IT

 

Role-based analytics helps the IT group automate reporting and analytical tasks for various functional groups so a company’s strategy is more quickly achieved. It eliminates the need to sidetrack valuable IT resources for consolidation of reporting data. IT is also freed from programming required calculations, which are handled behind the scenes with pre-built mathematical and statistical algorithms.

 

Because role-based analytics software has pre-built, predefined integrations, it can be deployed quickly and without the need for consultants and system integrators, which expedites return on investment. Prior to implementation, it is important for IT to work closely with executives and the role-based analytics vendor to thoroughly assess project goals within the context of existing data.

 

Also, to ensure a smooth implementation without delays, it is important to take the time upfront to understand what KPIs the role-based analytics software will measure. Companies tend to want to measure and analyze everything, when in actuality they should only analyze what directly correlates with the high-level strategy set by the CEO.

 

Over time, executives will inevitability change strategy in a way that impacts what KPIs are tracked with role-based analytics. In this situation, an IT administrator should be able to adjust the software so that new KPIs and their related data are added.

 

 


Christina McKeon is director of product marketing, Performance Management, at Infor where she is responsible for driving Infor's global performance management strategy. Key areas that McKeon focuses on include market positioning and messaging, and working with users, managers and executives within organizations to understand market drivers for performance management. She has more than 15 years of marketing experience. Before joining Infor in early 2007, McKeon managed product marketing initiatives at SAS covering business intelligence and analytics markets. û

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