SAP’s acquisition of Business Objects earlier this year is one more step in the business intelligence (BI) evolution — going from tools for expert users to a BI suite that supports an information-dependent, decision-making community and allows even novice business users to create actionable dashboards, analytics, and reports.
SAP is now more focused than ever on offering a scalable, holistic, and sustainable BI platform that addresses how enterprises manage, consume, or mine data for new opportunities. The technology is there — now it’s time to look at how your organization can make the most of its BI systems and improve its processes.
New BI software and tools are only the technical foundation for an enterprise information strategy. And every company has its pain points with BI, so this is an ideal opportunity to look beyond technological fixes and to implementing the right organizational and process improvements. Executive management needs to consider how to build a framework that ensures that the company can operate more effectively, efficiently, competitively, and successfully — for example, how to improve analytics in order to make better business decisions.
To do this, I suggest that you revisit your BI strategy to ensure that you can achieve the business goals you have set out with and that you are ready for the next wave of innovation. Ask yourself these questions:
- What has been challenging for us about BI in the past?
- How can BI live up to our high business expectations?
- How can we get reliable and consistent data, enterprise wide?
- Where can we use BI more effectively within our business processes?
- How do
we ensure that BI, business users, and IT can effectively communicate?
In responding, you may be tempted to create a list of quick fixes. But I recommend that you take a holistic viewpoint — looking beyond technical fixes and carefully evaluating your internal processes and organization as a whole.
I also recommend following a BI strategy that I’ve developed through many years of consulting experience, as well as managing BI departments, which included one very large SAP NetWeaver Business Intelligence (SAP NetWeaver BI) platform and a diverse set of non-SAP data warehouses.
3 Steps to a Sustainable BI Infrastructure
Technology aside, large and small enterprises need to transform themselves into process organizations. One critical goal of SAP NetWeaver BI technologies and applications is integrating BI information with business processes.
Enterprises need to take three steps to develop a successful process-focused global BI strategy:
- Obtain a single version of the truth. Optimize your data structures. Ensure that you have a consistent, global data and information framework to give you the competitive edge of powerful analytics for faster, objective, and effective decision making.
- Establish global governance. Manage your processes. Establish governance structures for BI systems to provide transparency into business processes and to operate from a global set of standards.
- Achieve business process-centric BI. Give users more direct access to key information. Target your business and IT efficiencies to redeploy scarce resources to value-added initiatives.
Step 1: Achieve a Single Version of the Truth
Getting to a single version of the truth (SVOT) is usually pushed as a purely technical challenge rather than a business transformation effort. Many enterprise systems do have data inconsistencies historically built in due to improper design, local vs. global systems, and mergers.
Therefore, companies spend countless hours during important business meetings trying to solve these discrepancies. As a result, they lose precious time trying to reach a consensus around business term definitions rather than analyzing the business results to better predict the future.
Building a global foundation for achieving an SVOT is necessary to efficiently run a company based on a common set of enterprise-wide assumptions. Proper classification is especially urgent for worldwide and complex enterprises with a diverse set of services or product lines across various markets. From a global perspective, inconsistent definitions result in unclear profitability results. Uncontrolled data growth often compounds this issue, making it almost impossible to gain insight into underlying problems.
According to what I’ve seen, the global market environment forces enterprises to address information challenges head-on. BI organizations need to be able to search for and access the data — from dashboards to analytics and reports — at lightning speed.
Start at the Highest Level
So where do you start? Two common culprits of data problems are customer and product data classifications. A good example is an inconsistently defined customer hierarchy or unclear product category by geography.
One company location might consider a certain client an independent retail customer, while at another site that same customer is part of a large retail chain. Or, on the product category side, a T-shirt resides in the “soccer” product category in one region and in “football” in another.
Many companies are overwhelmed by such an overarching goal for all their business data. I recommend starting with a top-down approach. Begin by focusing on aligning high-level corporate performance measures, such as your enterprise-level profit and loss (P&L) statements and goals.
This alignment should include the actual data definitions that are part of those key performance measures, but also any definitions that might be required for global alignment of:
- Corporate key performance measures, such as sales growth or asset utilization
- Components (products, customers, etc.) across geographies and business lines
- Master data and its attributes, groupings, and hierarchy definitions required to slice and dice or analyze the business flexibly, addressing present and future needs
Then Close In on Data Throughout Your Organization
Once you align the business definitions at this highest level, you can eventually repeat this process and push it down to the next level of the enterprise, then the next, and so forth.
With your enterprise-level P&L statements as a starting point, you’ll then move down the statements and define an SVOT release schedule.
In addition to rationalizing your data, this also provides a timetable for allowing IT to develop a scalable architecture (SAP NetWeaver Master Data Management, SAP NetWeaver BI systems, etc.). Note that this architecture needs to be flexible enough to be refined as you generate an SVOT.
Step 2: Establish Global Governance
For those companies that have established business process ownership or governance structures, this generally does not fully extend to “owning” key performance indicators (KPIs), performance measures, or analytics and reporting solutions. In fact, too often IT ends up owning a BI solution.
What I am advocating here is extending or establishing a defined business process stewardship. With a business process stewardship framework, you assign a person who oversees and is globally accountable for not only business processes, but also information point (KPIs, performance measures, or analytics and reports) mapping.
This mapping includes associated master data, elements, groupings, and hierarchies to facilitate the process of aligning definitions in their respective business process areas.
By establishing business stewardship and accountability, companies can ensure that the BI solution provides aligned and consistent information on a release-by-release basis. Furthermore, this framework provides a baseline understanding of business processes and definitions.
Step 3: Achieve Business Process-Centric BI
For this last step, it’s important to understand that business process-centric BI involves getting the right data into the hands of the right information consumers.
After an organization consumes information to make decisions, it needs to transparently integrate the resulting business actions across the company.
The reality — and the problem — is that often no one employee owns specific reports. In many cases, business analysts develop reports from huge data dumps created from various source systems. Then they disseminate the reports to the actual information consumers in your organization. This manual process is time intensive, often not automated, and typically not repeatable. This leaves business users with inadequate reports and without a way to quickly obtain the information they require in critical business situations.
As a result, IT or BI organizations often get blamed for “not delivering what the business needs.” At the same time, these organizations scratch their collective heads as to why that is the case, since solutions have essentially been delivered to business specifications. Today’s business analyst, therefore, has to transform from a report writer to a true analyst.
Integrating new BI user tools, such as actionable BI dashboards, analytics, and reports, with a service-oriented architecture (SOA) and developing full business process stewardship helps deliver decision-ready BI solutions, reduce business and IT development redundancies, and minimize IT system complexities.
Creating a BI Organizational Model
Once you have formed a sustainable BI infrastructure, you need to set up an organizational or process model in order to really make your BI strategy successful. To enable the business to increase effectiveness, both business and IT staff need to have a common operating model.
A business process-centric organizational model with clear roles and responsibilities should exist that addresses business and IT needs for fostering efficiencies. I recommend that you put business transformation efforts in place to take full advantage of the positive (and sometimes negative) impacts of BI.
The proposed BI organizational model is a framework for building and sustaining business process-centric BI solutions and implementing an SVOT in technical BI solutions. This model is the organizational heart, connecting business and IT far beyond the BI sphere.
Unlike other organizational models, it enables the development, deployment, and adoption of BI solutions directly by the information consumer while driving significant efficiencies.
The model is fundamentally a group of skilled business, process, and IT members all working to deliver business process-centric BI solutions.
The Business Group
The business group is organized by geographies, business units, or departments and is at the highest level of the organization. This group is deeply connected with the information consumer and is responsible for delivering business processcentric content.
The Process Group
The process group possesses the business process and information point knowledge within the enterprise, providing the BI organization with business process expertise. The business process steward heads this group and is also the facilitator for generating an SVOT.
The Architecture Group
The architecture group designs a sustainable BI platform (very much like city planners) as the technical framework for implementing an SVOT. This group also develops the architectural guidelines for designing business process-centric BI solutions and the underlying (enterprise) data warehouse(s).
The Technical Group
The technical group translates the BI solution into technical objects by leveraging the architectural guidelines. These technical objects include the data warehouse, master data, and the technical building blocks required by the business group for delivering BI content.
The Infrastructure Group
The infrastructure group manages the technical systems (such as servers), security, monitoring and administration, etc.
The BI organizational model also provides an opportunity for a co-sourcing dimension that’s flexible enough to consider enterprise culture and maturity.
Help BI Reach Its Potential
We all want BI to live up to its promise. Enterprises expect BI solutions to help them uncover new business opportunities, make more effective decisions, become more efficient while providing transparency into business processes, and explore the capabilities of new technologies, such as Business Objects solutions.
If you adopt the foundation proposed here, you will help your BI technology live up to its full potential. With this framework, your business can rely on consistent, complete, and actionable information.
The BI organizational model seamlessly integrates business and IT resources to a single point of contact for your business users — and helps you adapt to change at the speed of business.
Tips for Partnering Your BI Team with Your Change Management Team
It is imperative to partner enterprise change management with the BI organization in order to create a successful BI framework. The change management team is responsible for ensuring BI solution adoption.
Create BI solution adoption programs. These are the plans that map out how major BI solutions will be adopted, refined, and supported. These programs also ensure that information consumers accept new BI solutions and technology and foster alignment with the enterprise’s intended outcomes.
BI advancement is the catalyst for business transformation. As such, it changes the way companies do business. This requires change leadership activities to ensure that the BI business goals can be achieved. Specifically, you should align the change management team with the business process stewardship framework to support all three foundational elements of your BI infrastructure:
- SVOT activities
- Process improvements
- BI solution development
Sven Jensen oversees Sapient’s SAP NetWeaver BI practice, driving its strategic direction. He leads the development of new BI solutions and works on innovative BI implementation approaches. Sven is an accomplished technology and business solutions executive with over 15 years of experience in optimizing BI performance, introducing SAP solutions, and generating revenue/profit gains for industry-leading Fortune 100 corporations and clients.
Prior to joining Sapient, Sven was responsible for implementing a now 30+ terabyte single instance SAP NetWeaver BI solution at a Fortune 15 pharmaceutical wholesaler, and then served as the director of global business intelligence at a Fortune 100 apparel and footwear consumer products company. He holds a Master’s Degree in Computer Science from Frankfurt University and the University of Massachusetts Amherst.