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Better Decision Making with Proper Business IntelligenceQuality information is key to making quick, rational business decisions
BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney 1
As companies focus on growth and business development, the availability of quality information is crucial to making quick, rational business decisions. New technologies, however, can
cause information overload, leaving decision makers buried under a mass of irrelevant, inadequate, and inconsistent data. Some companies manage to provide their decision makers with precise, relevant data in an easy-to-grasp format. These companies have discovered the value of effective business intelligence capabilities.
For many companies, new technologies are causing information overload, leaving decision makers overwhelmed with inadequate, incorrect, incon-sistent and misleading information. Indeed, the various acts of retrieving and processing this often useless information can tie up numerous resources. Yet there are companies that manage to provide their decision makers with processed and automatically consolidated raw data, presented in an understandable, easy-to-grasp format. These companies provide insightful information for quick, profound decision making. What do these companies have that the others don’t? Business intelligence (BI) capabilities and processes. Business intelligence is a research field that focuses on theoretical and practical aspects of achieving a solid information basis for decision making. This paper summarizes A.T. Kearney’s experience in helping companies shape their data processes to obtain the right information for rational and quick decision making.
What Is Business Intelligence?Business intelligence focuses on the particular field of data processing and consolidation to retrieve
information for decision making. The overarching objective is to provide—via various solutions—the right knowledge to the right people at the right time. Doing this requires the right mix of IT systems, architectures, data structures, data- collection processes, and responsibilities for provid-ing meaningful information. Business intelligence has a proven impact on key performance indica-tors (KPIs). For example:• 60percentofexecutivemanagersstatethatthe
use of a performance management tool has a positive impact on shareholder value
• Return on equity (ROE) is more than twiceas high in companies that widely use perfor-mance management tools compared to those that do not in the same industry
When assessing BI capabilities, there are four levels to consider: Reporting. Reporting is a core functionalityof BI tools as the objective is to create recurring, standard, reports in an efficient and user-friendly manner. Reports are predefined and static bynature, generated either by request of an end-user or refreshed periodically through an automatic scheduler (uploaded on Intranet servers or shared
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Three Phases of Implementation A successful corporate BI implementation has three phases (see figure 1). In implementing BI sys-tems, it is important to begin with business requirements, because projects that are technically triggered usually fail. Phase 1: Define the necessary KPIs on a management dashboard. A key activity in the first phase is to define future reports and KPIs, which often means eliminating some existing reports, as many are unnecessary and do not truly reflect the company’s objectives (see figure 2).1 Next, is assessing data availability to calculate defined KPIs; a sound data basis is a key success factorforsystemimplementation.Externaltools
connecting to existing data warehouses and addi-tional calculations should be kept to a minimum. Also, the various layers of a BI system are evalu-ated to define which areas should be addressed and identify specific parts that should be elimi-nated (see figure 3 on page 4).
It is important to clarify at the beginning which areas shall be covered by the project: Is it a BI system for finance KPIs only or does it also include supply chain management? Will the proj-ect integrate other functional areas, departments or even specific business lines within operations? Oftenhumanresourcesandcustomerrelationshipmanagement (CRM) are the next candidates toimprove finance BI and integrate more of the
drives and accessible to a predefined group of cor-porate users). Key functionality is reduced to data consolidation and aggregation from various sources in a repetitive approach (automated, ide-ally) from trusted data sources. Dashboards. Dashboards contain high-level, aggregated strategic company data, inclusive com-parable presentations, and consolidated perfor-mance indicators. They include both static and interactive reports with data translated into graph-ics, charts, gauges and illustrations to simplify the communication of complex topics. Dashboards allow basic interactions (such as drill down, slice-and-dice operations to “play with the data”) and provide various levels of detail to achieve deeper insights. However, the explanatory power of dash-boards relies mostly on users’ interpretations. Analysis. At the analysis level, BI systems provide not only consolidated information that users can detail and filter, but also forecasts and trend analyses to develop new insights (based on the raw data). Analytics. At the top level of a BI system is automated intelligent data analyses based on sophisticated “fuzzy” logic and “neuro-fuzzy” sys-tems. Based on user-friendly but powerful func-tions, the BI system can retrieve meaningful insights while hiding the underlying complexity of data interpretation. “What-if ” scenarios and simulation functionality provide advanced, tai-lored decision-making support. The fundamental basis of every BI system, however, is the data base on which it operates. Basic systems focus on corporate financial data only, while advanced systems interconnect internal and external sources with qualitative and quantitative data. Advanced systems process the comprehensive data set using methods perfectly tailored to a firm’s needs and condense the findings into meaningful knowledge—hiding the complexity and selecting
only the maximum amount of input necessary to help executives make the right judgments.
The Advantages of Business IntelligenceWhen analyzing a business intelligence solution, it is important to consider the business benefits, including improved overall decision making and increased efficiency for business reporting and analysis. To this first point, BI offers four impor-tant prerequisites for proper decision making:• Requiredinformationisavailable• Dataisconsistentacrossorganizationalunits• Informationcanbeeasilyanalyzedusingbuilt-
in analysis functionality• Reportsarepresentedinauser-friendlyformat A well-designed business intelligence solution ensures that information across the organization is available in a consistent, reliable manner. Figures can be aggregated and compared in different business units, assuring the validity of like-for- like data comparisons, and that all management reports provide operations leaders and top man-agement with the information they need to steer the business properly. Essentially,BIimprovesefficiencyonboththeinformation technology (IT) side and the business sideoftheorganization.OntheITside,workersare freed from the recurring task of creating and changing data reports as end-users are able to create and change their own reports. On the businessside, less time is spent in data analysis and prepara-tion as management reports are created directly from the BI dashboards. Not only is the data in these reports more up-to-date and credible, but also they are easier to read and handle. And, impor-tantly, the information can be downloaded on smart devices, including the iPhone and iPad. The sidebar on page 4, What Makes a BI Leader?, offers a short list of success factors shared by top business intelligence organizations.
Figure 1Three phases of a business intelligence solution
Source: A.T. Kearney analysis
Phase 1
Define key performance indicators and level of business
intelligence to be achieved
Phase 2 Phase 3
Collect requirements, build prototype and conduct
vendor “proof of concept”
Implement solutionand improve tool
according to release plan
Figure 2The main tasks in Phase 1
Source: A.T. Kearney analysis
• Evaluate potential keyperformance indicators(KPIs)
• Analyze empiricial findings related to use of KPIs
• Evaluate simple profitability metrics
• Assess select KPIs for appropriateness
• Compare analysis of value-add KPIs
• Identify potential risks of making the wrong decision
Perform qualitativeevaluation
Determine valuecorrelations
Analyzerisks
Makerecommendations
1 Phase 1 should always be completed fully before proceeding with the second phase, as the required reporting and the defined KPIs set the framework for tool selection.
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business. The link to operations is more difficult as KPIs from manufacturing, production or logis-tics are fairly different from finance KPIs and are often difficult to connect to existing KPI trees. Even between similar business lines, KPIs aresometimes slightly different because they repre-sent different business models—for instance, internal production for intermediate products or external production for final products. If the long-term strategy is to analyze operational KPIs, this should be addressed at the outset. Once thesequestions are answered and all affected business areas are addressed, the second phase can begin. Phase 2: Create a design and navigation prototype and build a “proof of concept.” Four tasks are involved in preparation for system imple-mentation. The result is a “proof of concept,” designed before the comprehensive implementa-tion begins. At this point, software vendor selec-tion is independent of specific design requirements and often driven by strategic policies or IT land-scape requirements. Based on IT architecture rules, a short list can be devised up-front to select appropriate tools to fit the company’s require-ments, IT strategy and IT landscape (see figure 4).
Phase 2 is not only about collecting require-ments regarding the functionality of a future tool (navigation and analysis deep dives, for example) but also about report design, dashboards and tool functionality. One point must be stated veryclearly: A pure management “cockpit” or dash-board cannot replace the internal or external reporting. As a first step, it can be seen as a second channel (always available), but with a different level of detail (management adequate). All man-agement cockpit tools offer a reporting function-ality used to print-out the dashboard content. Replacing the completepaper-based internal (orexternal) reporting requires significant efforts as the detailed design of every single page is outlined up-front. Both the dashboard screen design and the report layouts, which cover all of the depicted content regarding historic numbers and compari-sons, among other things, finally get defined before the detailed concept is handed over to a system integrator for implementation. The real-ization of the screens and the corresponding KPI visualization are the main drivers of the system implementation and the testing. Therefore stabil-ity is required.
Figure 3Layers of a business intelligence system
Sources: Forrester, A.T. Kearney analysis
Delivery
Apps
Form
fa
ctor
PSO
Reporting
Performancemanagement
Supportapplications
Analytics
Discovery andintegration
Data
Infrastructure Network
Report mining
DQ – cleansing, profiling EAI / SOA EII ETL / CDC
Discovery accelerators
Adapters / tool kitsAccelerators / query optimization
BPM / BRE integrationBAM / CEP
Operational data stores (ODS), data warehouses (DW), data marts (DM)
Integration – third party applications
Services registry and repository
Streaming DBMS Search DBMS
RDBMS
In-memory DBMSHierarchical / XMLColumnar DBMS
Multi-value RDBMSMulti-dimensional OLAP
Usage analytics Statistical analysis Web analytics
Data / text mining Guided decisions NLP Guided search
Time series OLAP Operational DSS Predictive analytics
Servers Storage
MDM
SI
Indu
stry
ver
tical
app
licat
ions
Stra
tegy
App
lianc
e
Met
hodo
logy
Gov
erna
nce
BIS
aaS
Hos
ted
BI (
ASP
)b-la
yers
)
MSP
/ ap
ps o
utso
urci
ngCe
nter
of E
xcel
lenc
e
Ente
rpris
e ap
ps: E
RP, C
RM, S
CM, E
RM
BPO
eLearningECMMetadata-integration, repositories
Version control
Reporting: ad-hoc, analytical, productionSearch Geospatial
Advanced data visualizationAlertsDashboards
Collaboration Life-cycle Mgt. Localization QA
Strategy / objectives management
Metrics / KPIs Planning Scorecards
Interactive voice response, ATM, point-of-salePortals
Desktop gadgets Office suites Mobile Disconnected
Org
What Makes a BI Leader?
From our experience helping com-panies implement their business intelligence projects, we have found several common characteristics or “success factors” that differentiate the BI leaders from the followers. The BI leaders:• Defineandoptimizecorporate
report standards• Focusonthebusinessnotthedata
• Establishabalancedscorecard• Definecleardatadimensionsand
structures• Developamasterdatamanage-
ment plan• Establishcorporatedatagover-
nance and clear ownership of master data
• Usereportvisualizationinpilots• Leveragewebtechnologies
• Focusoncross-organizationalefforts
• Distinguishbetweenbusiness-driven and IT-driven projects
• Definethelong-termBIscope,from the beginning
• Realizeamobile version of business intelligence
Figure 4The tasks in phase 2
Source: A.T. Kearney analysis
• Perform assessment to ensure the need for a “cockpit”
• Conduct a brief cost- benefit analysis of the area and other potentially affected areas such as procurement
• Draw up a short listof vendors, taking into account industry reports and other external information
• Assess the options from an internal viewpoint
• Complete a list of business requirements and build a first simple PowerPoint prototypeto develop a “look-and-feel” of the final product
• Begin company-vendor discussions
• Help the vendor understand the client and ensure vendor receives timely feedback so to make quick improvements
Assessment Vendorselection
Requirementsand prototypes Proof of concept
BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney 7BETTER DECISION MAKING WITH PROPER BUSINESS INTELLIGENCE | A.T. Kearney6
The proof of concept increases the developers’ understanding of the company’s requirements before starting the real systems implementation. In our experience, a quick prototype allows a company to check the design of all possible pre-selected tools and test the capability of the poten-tial solution provider. Work packages can also be tested to assess vendors’ innovation capabilities in solving design questions. Finally, the firm’s requirements can be tested and challenged. Phase 3: Implementation. Implementation is a typical IT project. However, due to high visibil-ity and management awareness, the implementa-tion should be fast and provide quick solutions.
A release plan ensures first results are delivered quickly, while the final and comprehensive solu-tion is created in several steps, aligned with report-ing cycles and data availability. The first release should provide all required dashboard functions (design, navigation and drill-down) and some of the reporting requirements, which are detailed in the follow-on implementation phases and can be delivered sequentially. Typically, first releases lack the full data set. An essential activity in the BI project is to cleanse existing data and establish a process to record new data in a proper way, which often requires developing the entire data architecture, including dimensions, hierarchies
and formulas. Close interaction between system provider and business departments (as the final users and clients of the system) is crucial to the success of the project. The management cockpit or dashboard fulfills the design and functional requirements because it provides clear visibility to management and the necessary ease of use. Although all required data or KPIs may not be included in the beginning, they are provided throughout the steps.
Governance and the CIO’s RoleWithin a BI project, the corporate IT and the CIO moderate between the different businessdepartments that are involved, the internal IT group, and the software provider or implementer. A BI project is often driven by the finance depart-
ment as the key user due to corporate reporting and corporate management requirements; finance defines the main KPIs on a corporate level and ensures standardization across all different busi-ness models within the firm. OperationalKPIsareprovidedbythediffer-ent operating units and standardized to ensure that consistent content is reported to top manage-ment.TheCIOand corporate IT takeover therole of supporting KPI definitions by providing information about data sources, data availability and data quality. And they start the analysis on how a business intelligence tool could be used to fulfill high-level requirements (see sidebar: Business Intelligence: A Case Study). Part of the project involves defining future BI governance. This often means establishing a BI
Business Intelligence: A Case Study
The management team at a large German company decided to imple-ment a corporate-wide business intelligence (BI) process. The com-pany, involved in heterogeneous businesses, started with pilot units in its three business concerns, defin-ing financial key performance indi-cators (KPIs) to manage and direct the corporation. The management team knew that success would depend on cor-porate-wide definitions for its KPIs so they could be cascaded down to all business units. The project began with develop-ment of a basic management dash-board that provided a visual KPI tree to clarify the logical dependencies of the two main KPIs—and then illus-trating all the subsequent KPIs that flowed from them—and how they navigated through the organization.
Next, business-specific operational KPIs were added to the dashboard, a simulation tool was developed to provide units with a business-planning model to illustrate the dependencies between KPIs, and a BI tool-based reporting process was designed and implemented The IT work began during the final definition of corporate-wide KPIs and reporting, providing infor-mation about the availability of exist-ing data within the data warehouse. This was followed by the vendor and tool-selection process. A proto-type was designed, and software pro-viders were asked to use the design and business units’ functional requirements to develop a rough proof of concept. Immediately after the proof-of-concept presentations, the vendor-selection process was finalized and
implementation began. Within three months, the company had its first release, covering main functional-ities, dashboard design and naviga-tion, and first-reporting factors. The release plan took into account the main reporting cycles, and two sub-sequent releases were scheduled within the planned timeframe. Soon after introduction, the management team was delighted as user acceptance proved stronger than expected throughout the organiza-tion. When asked about the success factors, team members were quick to cite the top two: design and ease of navigation within the BI tool, and on-time delivery of the major KPIs. All in all, the company is now dedicated to using business intelli-gence to help steer it on a richer and more successful course.
• Through TOOL 1 WYSIWYG the dashboard can be handled
• Vendor 1offers functional building blocks for the storing of comments in the SAP BW
• Simulations can be saved; retraction through vendor 1’s own functionalities into BW backend
• Look-and-feel remains the same
• Comments and simulation can be executed early
• Either DataMart on machine two or WebService on machine one
• BOE Infrastructure for LiveOffice and reporting tool (phase2)
• Possible according to the demonstration; no information given on the interface builder; use of all graphic types possible
• Possible according to the demonstration
• Comments can only be used in the machine-three environment
• Possible according to the demonstration; simulations can be saved and retracted into the SAP BW
• Look-and-feel remains the same• Comments and simulation can be
executed early
• According to vendor, it can communicate with SAP BW 3.5
but not demonstrated
• Basic infrastructure on machine one has to be built anew
Figure 5Detailed analysis of BI software vendors
Source: A.T. Kearney analysis Full function
• Only static design possible; performance critical
• Use of standard BDS associated with performance issues
• Generally not simulation functionality
• Due to low performance on comments and the illustration of graphs, no usage possible in phases 1 to 2
• Executed on machine one, no export of the cube data needed
• None
Implementationdesign
Implementationcomments
Implementationsimulation
Transition from prototype torelease I to II
Connectivity to data
Hardware costs
Category On-board tools Vendor 1 Vendor 2
Very limited function
A.T. Kearney is a global management consulting firm that uses strategic insight, tailored solutions and a collaborative working style to help clients achieve sustainable results. Since 1926, we have been trusted advisors on CEO-agenda issues to the world’s leading corporations across all major industries. A.T. Kearney’s offices are located in major business centers in 37 countries.
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center of excellence led by the finance department that includes data governance with BI system maintenance authority. Corporate IT should be part of the change advisory board that assesses and evaluates change requests based on the capabilities of the system solution, while IT maintains tech-nology authority.
Choosing Tools and an Implementation PartnerBI tool selection is rarely a “green field” approach. The corporate IT strategy, system landscape and the main requirements regarding the BI level to be achieved are all guidelines in the selection pro-cess. Market research and analysts’ estimations can be used as support documents, but in most cases these analyses are too general and cannot be adapted to meet company specifics. Instead, external reports are typically used afterwards as support information to justify the short-list ven-dors or tools. The software vendor and implementer are the same in most cases, as only a few companies are able to provide a full business intelligence suite, connected or even integrated somehow to the mainenterpriseresourceplanning(ERP)systems,suchasSAPorOracle. A company-specific questionnaire and evalua-tion template allows the efficient gathering of key requirements. The main questions or key evalua-tion points should be shared in advance with the
short-listed software vendors to give them an opportunity to prepare the tool presentation and to answer all questions completely. The clearer the requirements are documented and described, the faster the selection process can be executed (see figure 5 on page 7). A rough prototype—such as a PowerPoint visual of the management cockpit to demonstrate key navigation functions and design-related requirements will help both sides understand the desired outcome and manage expectations. It is the basis for the later detailed design and concept, containing the description of each requirement. This and the more technical description of the existing landscape and necessary interfaces are the most relevant documents for the implementa-tion and build up to the kick-off for the system-implementation phase.
BI: A Must for Business Success A proper BI solution is a must have in today’s world. Companies in all industries are using BI systems for successful decision making. These companies beat their competition and identify new opportunities to optimize their businesses. They also reduce resources for manual effort and rededicate people to analyzing data and preparing decision memos. For companies that grasp the true potential in business intelligence, they should take action sooner rather than later—time, as always, is of the essence.
Authors
Alexander Martin is a principal in the strategic information technology practice. Based in the Düsseldorf office, he can be reached at [email protected].
Robert Jekel is a consultant based in the Zurich office. He can be reached at [email protected].
Edgar Simons is a consultant in the Düsseldorf office. He can be reached at [email protected].
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