My name is Erik Golden, and I'm VP of Business Intelligence at Golden Consulting. If you want to follow developments in the world of Business Intelligence (BI), you have to follow Business Objects, the global leader in BI software.
Business Intelligence is pretty hot these days and seemingly almost recession-proof, but as a result, there’s a ton of messaging around reports, data analytics, dashboards, performance management, planning, data integration, etc.
So, if you are one of those organizations that are looking to leverage BI for improving visibility into Key Performance Indicators across your business, how do you weed through all the messaging and determine “what’s a good fit for your business, today and for tomorrow?”
A couple of key points to focus on and compare with your needs across the business:
> Does the BI platform you’re evaluating integrate well within your data architecture and technology landscape?
> If you start out small, will this BI platform be able to support a larger BI implementation as your business needs grow? Is the architecture scalable?
> How intuitive is the reporting side of the system? Can business users adapt to the reporting tools, analytics and dashboards quickly and ensure adoption?
> Is the consulting company that makes the software going to be there for you when you need support? To develop cutting-edge solutions that will protect your initial investments and provide value down the road?
In our experience, most mid-market customers who successfully evaluate Business Intelligence and implement a BI platform that delivers significant
value short-term and long-term have answered "yes" to all of these questions.
Well, it's official: we’re now going to witness “true change” in the United States and, as a result, to some extent, the world too. Whether or not you believe that or voted for it, the question of how Business Intelligence responds to that change is certainly front and center.
So, what does that mean for the world of Data Analytics, Performance Management and Business Intelligence? The financial mess on Wall Street certainly seems to suggest that a more transparent system, with greater access to data, is better for everyone’s 401K. But what does this administration in DC mean to the overall pervasiveness of Business Intelligence, data access or the security of everyone’s data?
Take, for instance, these excerpts from Obama's Health Care Plan: “Inefficient and poor quality care costs the nation at least $50 to $100 billion every year.” And additionally, “Barack Obama and Joe Biden will invest $10 billion a year over the next five years to move the U.S. health care system to broad adoption of standards-based electronic health information systems, including electronic health records.”
And from Obama's Technology Plan: “To ensure that powerful databases containing information on Americans that are necessary tools in the fight against terrorism are not misused for other purposes, Barack Obama supports restrictions on how information may be used and technology safeguards to verify how the information has actually been used.”
Those are just two examples of how the new administration will look to change the American landscape and business environment, and I think the future of Business Intelligence solutions will be greatly influenced as they push on all fronts to make this country a leader in Business Intelligence-based solutions and improvements. The importance of being a data-driven company, to stay competitive, respond to regulations, enhance the patient experience, cut costs, and protect against fraud or provide for national security will be a big force in the area of BI in the next four years and beyond.
Whether or not you believe the statement “Yes we can” to the challenges put forth in Obama’s speech, the question will now be put squarely on those who develop and deploy Business Intelligence solutions to deliver into history the statement - “Yes we did.”
The amount of data within your organization is probably double what it was last year and maybe even more. This trend is only going to get steeper, and fast. Many IT departments have been adding data marts at a dizzying pace to offload the hit on transaction systems or core data warehouses, but the proliferation of data marts is going to have an impact on your overall data strategy and will throttle the long-term plan for organizational growth and the accuracy of your data.
Many of our consulting customers in the mid-market have begun to look more closely at the idea of Operational Business Intelligence in the form of an ODS (Operational Data Store) or replicated data as an alternative. Operational BI has been around since the mainframe days and has been in use in the larger enterprise customers for quite some time. Now, with the proliferation of data sources in the mid-market environment, setting up a data strategy that includes Operational BI in a mid-sized company is looking like a great alternative to a giant data warehousing project or data marts run amok.
There are certainly things to consider when looking at Operational Business Intelligence. An ODS may have some performance issues on your transactional systems when capturing data changes for consolidation. Data latency may also be something that needs to be addressed. In some cases, a replicated data source may be enough to get by, and so long as you don’t need to reformat the data, may be just the right step as an intermediate solution.
Modern technologies in Data Integration, Data Quality and Enterprise Information Management have provided the mid-market with all the tools necessary to set up a robust and scalable Operational BI platform that will support live, consolidated, replicated or federated data as necessary.
In the end, by making sure you have a solid data strategy that takes a good look at all of your Business Intelligence needs in reporting, data analytics and dashboards for performance management, and integrating those needs with your overall database and data integration capabilities, you can avoid some of the pitfalls of a graveyard of unplanned data marts.
Good information is based on sound data. In order to improve the bottom line, guard against compliance issues, or be able to make better decisions and leverage current Business Intelligence investments, organizations need to have access to accurate data.
For those who log into a dashboard every morning to monitor Key Performance Indicators, or work with analysis or reporting tools on a daily basis, the importance of data quality is painfully obvious. Many organizations have manual processes or semi-automated solutions to manage Data Quality and protect against errors in patient records, shipping to incorrect locations, duplicate billing or low inventory at a critical juncture. Integrating these stand-alone solutions into a Business Intelligence platform, however, is often difficult or unmanageable. Making sure that good data is available for an organization’s decision-making processes is a core aspect of quality control in any organization, and it should be a key component when planning a BI strategy.
Those organizations on the cutting edge of BI on the front end (with dashboards and data analytics tools) have finally begun to understand the importance of building an integrated back end to establish a solid data foundation and to support BI across the organization. In my Business Objects consulting, I've seen firsthand that planning out a Data Integration and Data Quality strategy as a key component of your BI roll out will greatly enhance the eventual success of your BI platform.
And why aren't more employees currently using BI tools?? In a recent IT survey, 51% cited integration issues with existing systems and 45% cited data quality issues.
Only further proof that you can lead a horse to water but you can’t make it drink...
POCs (Proof of Concept) are certainly a fact of life in the technology space, and have an important role to play for the end customer when it comes to selecting a Business Intelligence platform. However, planning out a POC is even more important to the overall process, as it can have a big impact not only on the BI tools that are eventually selected, but also on the Business Intelligence consulting firm that will be essential to a successful implementation. Too often a BI tool or BI consulting partner takes the blame for what is, in effect, a poorly planned POC.
Since BI is such a customized solution for each individual business, making the investment in planning a POC that maps to your specific data needs as a business is crucial. A couple of issues to consider when planning a POC:
1) Have a good understanding of the users’ needs. One of the core problems with BI implementations is the lack of quality requirements. Before bringing in a BI consulting partner, make sure you’ve got a good grasp of what type of data, reporting or analytical solutions you’re looking for from a BI platform. If you don’t know enough about what the business requirements or data analytics are, consider bringing in the BI consultants to do a preliminary assessment prior to executing a POC.
2) Make sure that you have a working test environment well in advance. It is awfully hard to make an honest evaluation of a BI tool set if you’re running it in an inadequate environment and it’s too risky to run it in production. It may seem like a basic step to planning a roll out, let alone a POC, but often times, when people are in a rush to get a BI solution in place, this problem happens and the results are never good.
3) Set an Agenda and secure resources. Prior to bringing in a BI consulting partner, make sure you have a POC on the calendar of all the appropriate business and IT resources. Having a predefined agenda—one with input from the BI partner, IT and the business users—is also something that will keep all of the participants focused and able to plan out day-to-day business activities around the POC. And, always make sure you have a large enough room with lots of white board space, a projector and any network access that is required.
4) Make sure that you have access to the right data. The difference between a POC and a custom demo is being able to leverage your own data—to really see BI tested in your environment and against your business needs.
The ability to chose the right Business Intelligence tool for your data, analytical or reporting needs is critical to getting the true ROI that BI promises. With the growing complexity involved in deploying BI, getting the evaluation process right is even more important than ever. Planning a proper BI POC is not rocket science--just something that often gets overlooked until the BI consultants are in the front lobby and you’re supposed to start in 30 minutes...
Since everyone knows how to “google” your favorite restaurant or vacation, the question these days is how to leverage the “Google” phenomenon within your business intelligence deployment and improve end-user data access. As the power of search capabilities continues to reach beyond web pages and into databases, metadata and transaction feeds, many are looking to search as the new front end to ad hoc query and analysis in BI.
Search in BI has the potential to shake things up even further by becoming the path to relevant data within reports and databases and integrating complex data sets on its own without the need for the standard data integration or ETL technologies.
Tools such as Intelligent Search from Business Objects are at the forefront of search capabilities for BI content. BI is no longer used by only handful of data analysts in finance. With the broad adoption of business intelligence and the need for access to data across the organization, look for more and more “Google” type qualities within your BI deployment for increased user acceptance and greater access to data.
With the growing demand to provide greater access to data, reporting and analytics to analysts and non-technical staff within the average mid-market business, the pressure to provide a clear BI strategy across the organization is increasing every day. For many IT departments in the mid-market, the decision between utilizing BI tools already embedded in individual applications that support the production systems, or breaking out the need for BI capabilities, supporting an agnostic BI platform and delivering access to a separate data layer is at the crux of this issue.
Unfortunately, this decision is bound to get harder as time goes on and individual applications such as Kronos, Meditech, Eclipsys and Sage continue to add increased BI capabilities embedded within their tools. These vendors will only turn up the heat by suggesting that it’s just that much easier to let users go right to the source and do their analysis directly off of their systems with these customized tools and predesigned views of the data. As business users become more and more data savvy, and as the need to do complex data analysis increases, these often unsupported groups will be drawn in even further by the notion of easy access to individual systems for quick data analysis.
This trend, however, will only increase the “silo’d” aspect of data and analysis and may even hamper an organization’s ability to truly see the forest for the trees and make better decisions more quickly.
As an alternative, many leading BI tools such as Business Objects allow access to any data source across the business. By leveraging the Business Objects Universe or meta-data layer, organizations can now begin to remove themselves from the growing dependency on data analysis from the application vendor itself. The beauty of the Universe is that it maps to any systems, whether production environments, data marts, data warehouses, and even unstructured data in certain circumstances. This provides a powerful alternative to constantly pulling data out of each system and dumping it into spreadsheets or access databases for aggregates and high level data analysis.
Many of our customers in the mid-market business are just now beginning to understand the overall advantages and flexibility that developing a meta data layer can provide. One CFO was even so happy to see how well the data could be managed across his organization that he even started to talk freely about replacing a few applications because he would no longer be tied to their outdated reporting solutions. Being able to make better decisions about your data is a big advantage, and becoming free from application dependency is one step worth considering.
As a Business Intelligence consulting partner to many companies in the mid-market, I get the opportunity to see BI deployed in a whole host of different ways and to address a wide variety of business issues. One thing I’m seeing a lot more of these days is the need to develop solutions for data visualization for non-technical users. More and more people need to make sense of data and to present that data in order to do their jobs more effectively. In the past the only way to cost-justify a sophisticated BI deployment that could support data visualization was because the underlying data required a heavy dose of data analysis or statistical manipulation in order to be useful to top line executives. Not so anymore. For today’s BI deployment, data visualization is now becoming a standard expectation and something every IT department must now support for a wide range of users.
So what are the issues you need to consider when rolling out data visualization tools like Crystal Xcelsius in any BI deployment and for non-technical users?
Here are a couple things to keep in mind when expanding a current BI deployment beyond the standard data analytics and operational reports.
First and foremost, keep it simple for starters. Make sure the data is described simply as this will allow for more natural analysis and generally deliver the most thorough understanding of the results. This is especially true when rolling out to a user base that is not trained in data analytics and advanced reporting techniques. While tools like Xcelsius are designed to make this process easier, it still pays to start with the baseline and work up rather than developing “eye popping” dashboards with lots of complex data points.
Second, choose a tool that allows you to transition between data visualizations seamlessly as well. Make sure you leverage the BI capabilities that enable a user to flow from salient point to salient point, rather than getting lost in and amongst the speedometers and gauges. One thing we always do here at Golden when delivering a dashboard solution, no matter what the size or complexity, is to do a thorough job of “story boarding” the layout in order to maximize the flow of analysis for business users. This may reveal breakdowns in one’s business processes or data models, but it’s critical to any successful data visualization project.
Lastly, what’s the point to visualizing data if we can’t turn something into a solution for the business? Given today’s complex world of data delivery, make sure that you choose a BI platform that will support delivery of data visualizations to all sorts of mobile devices and that will allow for maximum collaboration across your users. There’s a lot more out there in terms of BI collaboration that customers need to start leveraging in order to get the type of ROI they want from a BI deployment.
Today’s business users certainly need to simplify their data, and make sense of it in a visual manner, but that requires a little thought in planning out one’s BI deployment. Make sure you get the transition from making sense of data into presenting data in a meaningful manner and your BI deployment will be a big success for those new to the data visualization phase of
Many executives of companies in the mid-market are clammoring for dashboards and data analytics so they can stay lean and be more competitive, but making sure that they're meaningful and actionable is what will determine who's going to get the results they need. Now that technologies for business intelligence are becoming much more available to the mid-market customer, planning out a successful deployment is becoming the big difference-maker in whether or not a business intelligence deployment will provide the ever so crucial ROI that is needed for a mid-market company. Just hiring a consulting company to come in and build a set of flashy reports or dashboards isn't going to cut it when the company's financials are a mess or sudden growth is overwhelming production...
From our experience servicing mid-market customers as a leading Business Objects partner and provider of business intelligence consulting, the planning is the most important aspect of designing the right solution for the right reasons. Here are four high-level things to keep in mind when considering a dashboard or data anlytics solution for your mid-market company:
1) Data quality. Trust in the actual numbers is the most important aspect of any dashboard or business intelligence solution. Having people second guess what they see on a report when they drill into the numbers, or making a bad decision based on something that is displayed in a high-level metric on a dashboard or analytic is the death knell of most business intelligence initiatives.
2) Linking the metrics, reports or analytics properly on the dashboard. Making sure that, when an analytic is presented at a high level on a dashboard, that someone can quickly discern the proper relationship that data has with other relevant data is the key to making a dashboard truly actionable. Just knowing that "reimbursements" is a problem that needs immediate attention is only half the problem for the CFO of a local hospital. Understanding the impact to "cash flow" is the real kicker when you're trying to make an important decision in a small window of time.
3) Developing a culture of data driven decisions within the company and giving appropriate access to data at all levels. Getting a dashboard designed just for the CFO and the CEO won't help the organization improve its ability to drive decisions based more on fact and less on gut. To get true transparency of the business goals within the organization, people need to see the data that they must act upon and be given the tools to make good decisions. This does not mean that everyone in the business needs a corporate dashboard or access to complex data analytics, but everyone should have access to those reports or data points that will allow them to align their activities and decisions to the larger business goals.
4) Keeping the metrics and KPIs current and mapped to your business. Every company, especially those in the mid-market, undergoes change on a regular basis. Making sure that the data that you're relying on to drive business decisions is complete, current and organized in the appropriate data anlytics, reports and dashboards is a constant process. Redefining the KPIs or tweaking the analytics that your finance team is using because you just introduced a new product line, or aquired a company in a new region, is all part of the business of deploying an effective dashboard or business intelligence strategy. Nothing is more destructive to business intelligence than stale or incomplete KPIs.
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