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Business Intelligence Providers: Tips
BI is the set of techniques and tools for the transformation of raw data into meaningful and useful information for business analysis purposes. Business intelligence--BI is made up of an increasing number of components including: multidimensional aggregation and allocation, denormalization, tagging and standardization, realtime reporting with analytical alert, a method of interfacing with unstructured data sources, group consolidation, budgeting and rolling forecasts, statistical inference and probabilistic simulation, key performance indicators optimization, version control and process management, open item management. BI technologies are capable of handling large amounts of unstructured data to help identify, develop and otherwise create new strategic opportunities. The goal of BI is to allow for the easy interpretation of these large volumes of data. Identifying new opportunities and implementing an effective strategy based on insights can provide businesses with a competitive market advantage and long-term stability. BI technologies provide historical, current and predictive views of operations. Common functions of BI technologies are reporting, online analytical processing, analytics, data mining, process mining, complex event processing, performance management, benchmarking, text mining, predictive analytics and prescriptive analytics. BI can be used to support a wide range of decisions ranging from operational to strategic. Basic operating decisions include product positioning or pricing. Strategic decisions include priorities, goals and directions at the broadest level. In all cases, BI is most effective when it combines data derived from the market in which a company operates (external data) with data from company sources internal to the business such as financial and operations data (internal data). When combined, external and internal data can provide a more complete picture which, in effect, creates an "intelligence" that cannot be derived by any singular set of data.
Some considerations must be made in order to successfully integrate the usage of BI systems in a company. Ultimately the BI system must be accepted and utilized by the users in order for it to add value to the organization. If the usability of the system is poor, the users may become frustrated and spend a considerable amount of time figuring out how to use the system or may not be able to really use the system. If the system does not add value to the users´ mission, they simply don't use it. To increase user acceptance of a BI system, it can be advisable to consult users at an early stage of the DW/BI lifecycle, for example at the requirements gathering phase. This can provide an insight into the process and what the users need from the BI system. There are several methods for gathering this information, such as questionnaires and interview sessions. When gathering the requirements from the users, the local IT department should also be consulted in order to determine to which degree it is possible to fulfill the needs based on the available data. Taking a user-centered approach throughout the design and development stage may further increase the chance of rapid user adoption of the BI system. Besides focusing on the user experience offered by the BI applications, it may also possibly motivate the users to utilize the system by adding an element of competition. Kimball suggests implementing a function on the BI portal website where reports on system usage can be found. By doing so, managers can see how well their departments are doing and compare themselves to others and this may spur them to encourage their staff to utilize the BI system even more. In a 2007 article, H. J. Watson gives an example of how the competitive element can act as an incentive. Watson describes how a large call centre implemented performance dashboards for all call agents, with monthly incentive bonuses tied to performance metrics. Also, agents could compare their performance to other team members. The implementation of this type of performance measurement and competition significantly improved agent performance. BI chances of success can be improved by involving senior management to help make BI a part of the organizational culture, and by providing the users with necessary tools, training, and support. Training encourages more people to use the BI application. Providing user support is necessary to maintain the BI system and resolve user problems. User support can be incorporated in many ways, for example by creating a website. The website should contain great content and tools for finding the necessary information. Furthermore, helpdesk support can be used. The help desk can be manned by power users or the DW/BI project team.
Let us give you some tips for improving BI. BI can help inclusive financial institutions analyse enormous amounts of unstructured data to identify, develop and create new strategic opportunities, transforming raw data into meaningful information. Moreover, by gaining access to historical, current and predictive views of operations, inclusive financial institutions can gain insights that help determine the value their existing services are adding, to whom, and why(not), allowing institutions to improve product uptake amongst their target markets. CGAP, amongst others, has highlighted the relevance of using big data to drive financial inclusion: “using demographic and geographic information to decide who to target; and using income, credit history, age and other factors to make credit judgements.” With more and more data now available through electronic channels and generated in real time, BI tools are have the potential to drive more and more critical decisions. Just randomly extracting and reporting on data isn’t going to tell you much though, you need to leverage on BI as a strategic planning tool requires some forward planning: What do you want data to tell you? Today, it’s fairly easy to produce charts and graphs around collected data, but if it does not follow a strategic agenda it only provides information for its own sake. Start with questions: should we be doing XYZ? Are our products more successful with women or men? Has our marketing plan been effective in certain areas and demographics, and why? By starting with clear goals, your data can reveal solutions and reveal faulty assumptions to conclusively tell you whether you’re right or wrong. 1) Put a solid governance foundation in place: In order to use data to improve operational efficiency and gain a competitive advantage, organizations need to understand what data is available from internal and external sources, as well as the value this data has on process improvement, decision making, and development of new products or services. BI governance covers rules and processes pertaining to report creation, ownership, distribution, and usage. 2) Prioritize your goals: Know your options and match them to your goals. Some BI platforms are free, but take a longer time to properly set up. Others are subscription-based, but can be installed in a much shorter time span. Determine whether your objectives are more focused on cost or time concerns. Start small with one or two goals, then add additional goals once the initial integration is complete. 3) Identify key metrics: Before implementing BI software, it is a good idea to determine what data you need and what format you want to receive it in. Look for technology solutions that can deliver clean data with actionable insight. 4) Establishing a data warehouse isn’t enough: Work towards a data strategy that combines a data warehouse with the ability to synthesize and organize that data into the applications where it’s needed, and apply data visualization capabilities. 5) Use the right tool for the job: There are so many types of visualizations available; it is often difficult to know the right way to display information. Here are some of the most commonly used visualization types, and how to use them: Bar chart is used for comparing one measure, Scatterplot for comparing two or more measures, Line chart (or time series) for tracking data over time, A map for geographic data, A table for detailed data. Every good data strategy starts with clean, consistent data culled from across the organization. Ask yourself: What data is the most important, and what do I have available? It’s critical to identify the areas of the business where analytical decision making will have the biggest impact, and focus on those. With the above tips in mind, you should be well on your way to improving BI for your organization.
Time spent researching, implementing, and maintaining your BI investment can snowball quickly and mistakes are often expensive. Your time is valuable – save it by learning from other experiences. We’ve compiled the top ten tips on successfully implementing BI software from professionals who have already taken the plunge. 1. Prioritize your goals: “Know your options and match them to your goals,” says Boris Kontsevoi, President and Founder of Intetics. “For example, some BI platforms are free, but take a longer time to properly setup (up to 4 weeks). Others are subscription-based, but can be installed in a week. Do you care more about the cost or time?” 2. Recognize your non-negotiable criteria: Harold Leusink, CEO of Peritas Solutions advises, “Before you even start looking at solutions, separate out your ‘musts’ from your ‘nice-to-haves’.” Peritas Solutions, a consulting firm that has been helping companies find insight in their increasingly large data sets since 2001, finds that “your musts are non-negotiable, and so should be the first thing you talk to vendors about. Your ‘nice-to-haves’ give you a set of criteria you can use to objectively judge any solutions that passed through your musts filter.” 3. Utilize built-in tools first: “Opt for built-in analytics,” says Christy Delehanty, Content Lead at PandaDoc. “Instead of piling apps on apps on apps, try to make use of the analytics built in to the tools,” suggests Delehanty, “often, these dashboards provide the simplest peek at actionable data with the least set-up on your end.” 4. Clean data only: “Make sure you data is clean,” warns Jamie Lin, CEO of Gizmo Global. “This is obvious, but the biggest issue during implementation. Cleaning your data before you implement makes the entire project easier.” Chandra Siv, General Manager of Data and Analytics Solutions for North America at Mindtree, agrees that addressing data quality is a must. Siv adds that “the confidence level and trust in the data used for decision making is a critical success factor.” 5. Identify key metrics beforehand: “Before implementing BI software, determine what data you need and what format you want it in,” adds Gina Cerami, Vice President of Marketing for Connotate. “Look for a technology solution that can deliver clean data with actionable insight. Web extraction and monitoring solutions go hand-in-hand with BI and fuel informed decision-making.” “Know what you are trying to show before you start,” says Jon Mills, Director at Paige Technologies. “It is easy to get caught up in the rabbit holes of correlation instead of causation if you don’t have clear metrics in mind before you start.” 6. Start small – choose a few goals to focus on in the beginning, then add more: Michael J. Smith, CEO for Raster Media, advises companies to “focus your BI integration on one or two objectives initially.” In Smith’s experience, “this will speed up the integration and allow the integration team to focus their efforts rather than being overwhelmed with delivering results for dozens of objectives. Additional goals can be added once the initial integration is complete.” 7. Don’t ditch currently effective processes without reason: “Evaluate which tools and functionalities will actually benefit your company and ensure your entire team is using only those that you’ve determined are valuable,” says Sam Zietz, CEO of technology company, TouchSuite. “Although every tool in BI software was added to that solution (because) there is a need within the industry, many businesses already have successful processes in place that make those tools obsolete. In this case, implementing those tools might actually work against your company, particularly if some team members are inputting information in one system and others within the new BI solution.” In order to maximize productivity, Zietz says to “make sure your team is clear on which tools should be utilized and which should not be accessed within the solution. If applicable, you may want to consider putting administration locks on those systems within the solution that you do not want accessed.” 8. Make the technology work for you, not the other way around: “Make sure that you align activities with corporate strategy,” says David Reischer, Chief Operations Manager for LegalAdvice.com. According to Reischer, “the key is to extract useful information when needed.” 9. Empower end users by simplifying the toolset and infrastructure: “You’ll never be able to gather all the requirements from the users of BI so they need to be empowered to create, change, and filter reports in order to meet their BI needs,” says Craig Abramson, Marketing Director for Third Wave Business Systems. However, “if the infrastructure is too complex then data anomalies are inevitable,” Abramson warns, “complex toolsets take away the user’s ability to be self-sufficient.” 10. Don’t just stop at a more BI: “BI is about better intelligence, but then what?” asks Stuart Easton, CEO of TransparentChoice. Easton says “that intelligence is fed to a group of people to make a decision and that’s where the value generated by better intelligence gets diluted by poor decision making practice. Without addressing better decision making, any investment in BI is going to have a very limited impact.”
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