Is It Time to Evolve from Spreadsheets to Business Intelligence?

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1 Position Paper Is It Time to Evolve from Spreadsheets to Business Intelligence? Gregg Gordon Sr. Director, Big Data Practice

2 No matter how your organization delivers value to your market, customers are demanding improved service levels, perfect quality, and innovative answers to new problems. Customers today have more choice than ever and if a company fails to meet expectations, they will find an answer from a competitor. Of course, this isn t a new story. Organizations are always searching for an edge to create better value for their customers for example, technology has automated many business processes, allowing organizations to reduce errors and waste, speed delivery, and improve product and service quality. One result of process automation is the rapidly increasing volume of data that is generated from software and equipment that provides significant information about the inputs and outputs and how that process performed. Automation has not only sped up processes, it has led to reductions in labor, creating a situation in which fewer employees must make decisions in a shorter period of time. This has created a challenge and an opportunity in organizations because the workforce can no longer observe how a process is running and react to that. Instead, it must depend on data to understand what is occurring. Organizations that improve their use of this increased amount of data to make better, faster decisions will have a competitive advantage over those that don t. When you should assess your labor analysis strategy Based on the experience of helping thousands of customers improve their use of software- and hardware-generated data, Kronos has identified the activities that typically indicate an organization needs to move to a more formalized business intelligence strategy. Whether a company is facing a specific business condition or wants to find new methods of improvement, business intelligence provides insights to data that unlock the answer. If any of the following conditions apply to your organization, it may be time to consider a labor business intelligence strategy. How are frontline supervisors using information to make daily decisions? Do several different reports need to be pulled together? Do supervisors have to return to their office to access information? Is the available information different based on the location or department where they work? What s the latency from the time data is generated to when reports and analysis is available? One example of a common report that is challenging to create manually is a labor costing report, since it requires reconciliation of labor and production data. Are valuable reports that are critical to decision-making used only sporadically or even ignored? How large is the backlog of requests for custom reports? Do midlevel and lower level employees have to go through layers of approval to obtain information or get into the queue? Are departments limited in their ability to communicate and collaborate because they have limited access to the data generated outside their departments? When an executive calls into a department with a question, is it difficult to obtain the detailed information that was used to generate the report? These are all signs that an organization s reporting and decision support strategy needs improvement and that a business intelligence solution focused on labor may provide much-needed help. 2

3 For most companies, improving decision making is unlike anything they have done before. Automating production and business processes has become relatively common, with well-described best practices as well as suppliers and consultants providing solutions. When it comes to decision making however, everything changes. Using data to support business decisions encompasses not only the simple day-to-day decision making of if this, do that, but also the more complex area of planning, performing what-if scenarios, analysis, and problem solving. Business intelligence tools and Big Data techniques may be hot buzzwords, but their tools and techniques have not been widely adopted. Instead companies find themselves mired in many different forms of custom reporting, including standard reports delivered by software applications, spreadsheets, custom SQL extracts, and specialized reporting tools. Complicating things further is the reality that decision making can vary significantly from one department to another. Different data may be required, analysis requirements differ, and the availability of support changes by the level of priority. In this paper we will examine why business intelligence has not replaced the myriad approaches companies are using today. We will then look at how Kronos has approached using business intelligence in a more effective way to improve a company s ability to utilize its labor data more effectively and achieve competitive advantage. Why is building and maintaining custom reports so difficult? At some point, the standard reporting delivered by a software application falls short often when reporting requirements mean pulling data from two or more sources. At this point, the journey into custom reporting begins. Spreadsheets are undoubtedly the most common tool used in custom reporting and analysis today. Their ease of use and flexibility has made them a go-to resource in almost every organization. Like any tool, spreadsheets are great at certain jobs, but less effective as they are extended beyond their intended capabilities. Spreadsheets struggle to handle large volumes of data without slowing performance. Their use of pivot tables to slice and dice information is perfectly acceptable for an analyst who lives in the data, but notoriously difficult for a casual user. Spreadsheets are prone to error, whether through accidently entering the wrong data or because of how the spreadsheet creator decides to make assumptions and display results. As a result, users of the data are often subject to multiple versions of the truth. Spreadsheets are challenging to distribute and secure. Since they are primarily designed for individual use they have limited functionality for distributing and securing data across an enterprise. Finally, spreadsheets have no extraction, transformation, or loading (ETL) functionality to move data around from various sources. Data extraction and transformation is often a company s largest challenge. If there is any doubt about this at your company, just ask the person responsible for creating reports or extracting data. They typically have a very large backlog. 3

4 Obtaining and transforming data is often considered to be percent of any reporting or analysis project. There are common causes for this and they are interdependent: Reports are often built from more than one data source and generated from transactional applications such as Enterprise Resource & Planning (ERP), Timekeeping or Human Resources Management systems, or any of the other solutions that automate business and manufacturing processes The organization of transactional data is optimized for highly efficient input and output in small quantities There is often significant logic for interpreting data within the application that is not available to those trying to extract the data for other purposes, such as reporting The data is not clean. By their nature, transactions are discrete, allowing them to not interfere with each other if they re not perfect. Reporting and analysis requires much cleaner and consistent data elements To improve the performance of the transaction system and minimize hardware requirements, the amount of data stored within their own individual database is limited This optimization of data by each transactional application and the increase in unstructured data is the root cause of the reporting and analysis challenge. The custom report writer must: Translate business requirements into metrics and data requirements Understand the data model of the transactional database and the logic behind the values in the data Troubleshoot existing reports due to exceptions in the data that are introduced by users or logic in the application that the report writer had not seen before in previous data sets Carefully craft the SQL calls so that they don t impact the performance of the transactional system Maintain reports as the versions of the application change and the data model evolves Implement a security and distribution model to make sure the appropriate people see the appropriate data Begin storing data somewhere else in order to generate reports, including data over long periods of time If unstructured data is required, determine the patterns required to extract value from it Manage internal customer expectations about report development limitations and timeframes What does Business Intelligence provide that custom reporting can t? The shortcomings of spreadsheets and the need for clean, flexible data models gave birth to the Business Intelligence market. Business Intelligence applications have been very successful because when they are fully functional they deliver high levels of value. Here are some functional examples of what Business Intelligence can do that is difficult for a custom report writer to accomplish: Provide many built-in SQL functions that allow the data to be manipulated in various ways: summing up, drilling down, looking at flexible time periods, projecting future values, calculating new metrics, and statistical analysis to identify patterns and relationships Store and report on large quantities of data without impacting source systems Provide visualization capability that allows large amounts of data to be easily interpreted Incorporate flexible dashboard design environments that allow the organization of many reports and graphs by role Provide a security model to limit who has access to what data Optimize the way data is organized and presented so that one set of data can be used by a broader set of users 4

5 Deliver a highly interactive interface using features such as prompts, filters, drill downs, thresholds, and alerting Provide a simplified report building interface that doesn t require technical knowledge, reducing the load on technical staff and speeding time to information But even with all this power and efficiency in delivering information, business intelligence systems have not been widely adopted. It s not uncommon for a business intelligence system to be purchased by an organization to solve a specific challenge, with an eye toward expanding its use throughout the organization over time. But for many companies, years go by with little progress. Two challenges come into play: the first is access to the data required to report and analyze on a given topic. The second is the scarce human resources available to take a business problem and use the available data to solve it. Ready-to-use data and a library of solutions Kronos recognizes and addresses these challenges in two ways. First, we provide significant amounts of data from our transactional database in a ready-to-use format. Second, we have developed a library of ready to use Plug-ins that solve common labor-related business problems. Preparing data for use in a Business Intelligence application is the largest and most resource intensive part of making the solution operational. ETL handles the major cleansing, organizing, and calculating operations, which are the same steps that create stumbling blocks for custom report developers. By making transactional data available in a business intelligence environment, Kronos can reduce or eliminate the individual development efforts required to prepare data, thereby dramatically reducing the time and cost of getting a Business Intelligence environment operational. In addition to the economy of scale that comes with a Business Intelligence provider delivering the data, Kronos has additional advantages that customers can benefit from: Understanding logic in the transactional application so data cleansing is primarily limited to those exceptions generated by user input Access to a broad set of user requirements so that it can provide the pre-defined attributes and metrics used in reporting and analysis that most customers want Visibility into the specific transactional data model changes ahead of application releases so it can adjust the ETL process, ensuring reports continue to work as designed The ability to develop a sophisticated method of trickling incremental data out of the transactional database without impacting performance The ability to pass the security model from the Kronos Workforce Timekeeper application to the Workforce Analytics application so there is no incremental maintenance of security profiles Metadata layer that provides business terminology to describe data rather than using the technical table and column names, as is often found in do-it-yourself ETLs With Kronos developing and maintaining the ETL, customers save percent of the effort of their Business Intelligence project, improving the ROI, and providing more data to end users than an internal project could ever hope to achieve. 5

6 This pre-built approach still leaves data work to be completed with each project. Often external data, such as production results, must be merged with labor data to understand the impact of labor on the business. While this takes effort, in terms of labor reporting, only a small slice of operational data needs to be sourced and reconciled with the cleansed and organized Kronos data, keeping the project scope reasonable and still delivering significant ROI. With the data in place you can begin delivering high-value information to managers and employees faster, more consistently, and less expensively. The data is cleansed and available, do you have the resources to analyze it? Business Intelligence solutions offer many development features, from plug-ins that support R (a popular language for programming Big Data analysis), to simplified report editing, and formatting tools that allow relatively non-technical users to create reports and dashboards on their own. If you visited an organization that has created a datamart full of cleansed and well-organized data and asked who is creating reports and analyses you most likely would find a Business Intelligence Analyst. Larger companies and those highly dependent on data might also have a Data Scientist. These employees are still required to take business requirements and map them to the data available to create solutions. They typically have strong technical skills in order to understand the way data is organized and make changes or additions to the datamart.employees who have deep knowledge of data structures and the technical ability to edit schemas and data, create filters, attributes, and metrics, and apply algorithms that solve business requirements are relatively rare and usually command a high salary. A shortage of qualified candidates leads to another of the bottlenecks that prevent Business Intelligence applications from being widely adopted. This creates two challenges. First: companies are forced to prioritize their efforts, and often focus on creating dashboards and sophisticated analysis for financials and inventory. Middle management might only have access to status reports and not the insight needed to make forward-looking decisions. Without guidance from the business intelligence application, employees revert back to the technology they understand. Spreadsheets continue to proliferate and analysis is performed on data that is easy to access rather than the best fit. Closing the last mile in business intelligence To close the gap between a technology application and a solution that benefits your organization, Kronos has gone what is commonly known as the last mile. Because Kronos focuses solely on workforce management, it understands the business problems that HR, Payroll, Operations and Finance face when it comes to labor. Our workforce management suite is the most complete source of labor data in an enterprise. With these advantages in place, Kronos has added a number of complete solutions embedded in its product, as well as extended solutions known as a Plug-ins, that leverage both the data and the business intelligence technology. A Plug-in is a bundle of data, reports, and dashboards that solve a specific workforce-related challenge. It is a miniapplication that uses the functionality and data contained within the Kronos Workforce Analytics application. It s what a Business Intelligence Analyst or Data Scientist would create if they had the time and expertise to focus on workforce management problems full time. 6

7 As an example of a complete solution included with Workforce Analytics, the Workforce Auditor analyzes what is known as dark data. This is data that is typically not viewed by the user of a software application. In this case Workforce Auditor is looking at the audit trails of timecards and schedules. Each entry represents any addition, deletion, or edit made to a timecard or schedule a small trade of time and money between an employee and the organization. But in aggregate, these trades represent significant amounts of time and money. Additionally, they are used as evidence of inappropriate behaviors on the part of an employee or supervisor. The challenge for companies is that often these edits accumulate to millions of entries a year. 99% of them are legitimate changes. But what about the ones that represent a policy compliance issue, fraud, or abuse? Auditors often comb through these looking for these situations, but this is a difficult and laborious project. More often, the aggrieved employee shows the company the way after they file a grievance or lawsuit. What if there were a way to simplify the audit process so that potential issues could be identified sooner? Workforce Auditor solves this challenge. By using big data techniques, it identifies clusters of activities that are different than others. By focusing on these outliers, the challenge of digging into the details drops dramatically. Customers who use this today have found examples of employees fraudulently changing their timecard to increase pay and supervisors modifying timecards to avoid paying overtime to employees. In addition to abuse situations, companies have identified situations where managers are working around the system because the processes are not working for them. Understanding this allows the company to improve processes and educate employees proactively rather than wait for costs to rise or performance to drop to a point where traditional reporting catches it. Those that don t take advantage of this data will have higher costs and an increased risk of policy compliance issues. Additional plug-ins are also available to analyze and provide guided decision making for other types of labor-related situations, including Workforce Planning, Labor Costing, Absence Analysis, Scheduling effectiveness, and Store Performance. Each plug-in is an integrated solution that uses data to improve discovery and decision making around a specific set of workforce challenges. Because they are delivered by Kronos Professional Services and Kronos Partners, they can also be extended to provide individual tailoring based on an organization s unique needs. Kronos is using its access to data through its automation applications and understanding of workforce management to provide a complete business intelligence solution. From data collection through process automation to data cleansing and transformation, to reporting, analysis, and guided decision making, Kronos is able to provide customers with a significant business intelligence advantage when it comes to workforce management. Kronos Incorporated 297 Billerica Road Chelmsford, MA , Kronos Incorporated. Kronos and the Kronos logo are registered trademarks and Workforce Innovation That Works is a trademark of Kronos Incorporated or a related company. For a full list of Kronos trademarks, please visit the trademarks page at All other trademarks, if any, are property of their respective owners. All specifications are subject to change. All rights reserved. CV0456-USv2-EN