As businesses struggle to understand and effectively use the growing volumes of data they are collecting, they face a wide range of challenges in designing and implementing an effective Business Intelligence (BI) strategy. It takes hard work to develop a BI program that successfully produces data-driven business decisions.
The first challenge is defining a solid BI strategy that meets the needs of the business and delivers a return on investment. This is immediately followed by the challenge to secure the approval and funding for a Business Intelligence program. BI managers are faced with the task to find the right balance between agility, governance, and useful data. Faster time to insight can provide a competitive advantage, but this needs to be balanced against data security and privacy concerns. Useful, accurate data is key so business users can answer the questions they have and not perpetuate inaccurate analysis.
Business Intelligence initiatives require significant investment and are usually launched to address specific needs and fill existing gaps. Even though these goals may be clear to all the stakeholders, the inability to define the right tactics for achieving these goals can lead to a lack of collaboration, underachieving desired results and a lack of BI program adoption.
The first step is for organizations to accurately define the analysis or reporting problems they are trying to solve with the help of BI. Once this is accomplished, then they can identify the right Business Intelligence solution that suits their requirements. Devising an effective BI strategy before adopting a BI solution is extremely important. Choosing the wrong tool can lead to failure in the adoption of the BI solution.
Data Issues (Combining unintegrated systems with valuable data into one data model)
Business Intelligence applications are only as accurate as the data available to them. Organizations may spend substantial amounts of time, money, and resources into data investigations in an attempt to solve all data reporting issues at once. This typically results in failure. BI data design should be focused on a small subset of the data issues, the ones causing the most pain. Small, focused BI steps are key to a successful BI program. It is the classic application of the phrase “Eat the elephant one bite a time.” Small, reasonable goals achieved in succession are a key strategy for BI program implementations.
Fortunately, modern BI tools can blend and merge datasets from multiple sources without the need to rebuild databases or setting up a data distribution center. This enables businesses to start small and interface data sources as they implement their BI strategy in a phased approach.
Manufacturer Overcomes BI Challenges
A world leader in manufacturing industrial pumps, valves, controls, seals and managed services in industries such as power, gas, chemical, and others – realized that the standardization of reporting was necessary. The company had multiple systems and methods of reporting where there was no single source of truth. The key indicators that should have been consolidated and consistent were being reported differently by the departments. Time was being wasted on communication and translation of technical information as the IT department acted as an intermediary, taking requests to create the reports that were needed.
The company’s goal was to empower its employees and decentralize BI so that end users could have hands-on access to data and discover what’s relevant to them at their function. They wanted to remove the time-consuming manual reporting that continuously led to reactive decisions. The objective was to put power in the hands of the executives who could run a report on the spot to make decisions based on accurate data.
Following BI best practices, building the right foundation for the company to grow its data platform was essential. With the help of the right strategy, a consolidated data platform was formed that enabled the users to view and act on data from across the organization.
These best practices allowed the company to achieve operational efficiency as they went from tedious repetitive work to an automated solution. The new BI systems removed layers of complexity and increased speed when it comes to decision making as the end users can now run reports with a single click.
Coca-Cola's Unique Data Challenge
At the Coca-Cola Company, putting together useful data sets is a challenge. The company's distribution model involves a network of hundreds of independently operating bottlers around the globe. Each bottler uses Coke concentrates to make and bottle Coke’s wide assortment of drinks. The independent bottlers send data to Coke and Coke collects this data into a common system. This data is used to review production and sales to project future sales trends.
Coca-Cola collects a wide range of data which includes multi-channel retail data, customer profile data from loyalty programs, social media data, supply chain data, competitor data, sales, and shipment data from bottling partners as well as transaction and merchandising data.
Coca-Cola’s BI strategy takes a broad, visionary approach instead of a tactical approach with big data. Coca-Cola created a shared services center for all their data, meaning the data is combined centrally and made available through various shared platforms across the organization. This allows the company to use the data to improve their business process, products, increase their revenue, and reduce their costs.
BI Implementation Best Practices
Proof of Concept, Agile Development: As with most software projects, the lure of solving big problems with a grandiose design can easily lead to large cost, small benefit projects. To avoid this pitfall, many BI implementations start out as a proof of concept project. A business will define a small, defined area that needs detailed data. A small proof of concept team will be created to design and implement the BI process. As a part of the proof of concept process, an agile software development approach is also beneficial. This allows the team to incrementally design and develop the BI data, reports, and processes to address the problem.
Develop Usage KPI: Once the proof of concept version is complete, it is rolled out to the larger user group for use and feedback. A key process to determine the success of the design is monitoring the end user usage of the BI tool and processes.
Change Management: A formal Change Management process is required for all phases of the BI program. This includes the Proof of Concept phase. Communicating to the business user community - the BI strategy, implementation approach, phased schedule and expectations for use are all extremely important. Change management is key to a successful transition from an IT legacy reporting process to the BI supported data-driven decision process.
End-User Training: New technology solutions require user training programs. The best strategically focused BI programs can fail without a successful rollout and training program. It should be noted that BI training and BI change management related programs require the support and involvement of business leaders to be successful.
BI Consulting: Some companies have well-defined requirements, a sound BI strategy, and the right BI tool, but lack the technical skills to design, build, or maintain BI applications. This results in BI applications that have performance problems or deliver uncertain results. Software and business conditions continually change, and maintenance may not be a good use of internal resources. Also, over time, highly skilled internal resources leave the firm or retire. Engaging a consulting company mitigates these long-term risks.
Justifying the ROI of Business Intelligence
Determining the Return on Investment (ROI) of a BI solution is one of the most difficult parts of the BI process. Determining the ROI is made easier by defining the reporting gaps or data analysis difficulties that the business users are facing. The first step is to define the roadblocks and hurdles that prevent timely data-driven decisions. The direct benefits of BI implementation do not encompass the indirect benefits which are difficult to quantify. However, with the rise of self-service analytics through BI platforms, the cost doesn’t have to be a Business Intelligence challenge.
As you might have realized by now, BI solutions can be significant game-changers. To get closer to a determination of the actual value of the BI project, however, you must ask the following questions:
- Is it possible to quantify the business value of the BI Project for all Phases?
- Will the company see financial returns and can those returns be quantified?
- How soon will the returns be realized?
As with any software investment, a business wants to efficiently and effectively provide process solutions. Being able to define the problem and determining how BI can help resolve it is the first step in calculating the return on investment.
Many businesses do not possess the BI expertise needed to develop and implement BI systems. Many software companies are adding BI enabled data processes to their systems. Finding a software or services partner who has experience in the BI arena is a great first step in developing a BI strategy.
Your phase 1 BI strategy should be to target a small, well-defined area for BI implementation. Using the proof of concept phase with an agile software development process limits the risk of missing the solution goals, overspending and underachieving the projected ROI. A successful phase 1 will also build internal confidence towards the BI solution and this confidence from the business leaders and data consumers will be critical for the successful implementation of the entire project. In phase 1, monitoring usage of the BI tool and processes is a key success factor in BI implementations. If you build it and it is not used, the BI implementation has wasted time and money.
Don’t underestimate the role of change management in a BI implementation. The BI data and processes should enhance the current reporting and decision-making processes. Following a phased transition process significantly improves the odds of implementing a successful BI program.
Developing a solid BI strategy and seeking guidance in developing the program, businesses can harness the true power of data-driven decisions that can provide improved business processes, better results, and measurable business value.
MAJIQ Elixir BI Enablement
MAJIQ, has over 30 years of industry experience in optimizing paper, pulp and nonwovens business processes by reducing waste, streamlining operations, and dramatically improving order fulfillment. MAJIQ delivers software for life.
MAJIQ has partnered with Microsoft’s Senior Data Modeling Experts to design the Elixir Business Intelligence module. This module correlates and transforms Elixir data into an efficient tabular data model for plug and play use by Business Intelligence tools such as Microsoft’s Power BI. This gives the Elixir business analysts the ability to handle large amounts of data with high performance results. They can take their Enterprise Decision making into the future with Elixir - Software for life.