I recently had the privilege to share a presentation on business intelligence at the AIA’s CFO Large Firm Roundtable meeting in Charleston, SC. This presentation was an offshoot of a white paper on which Deltek recently collaborated with ZweigWhite and Deltek customers that covered decision making and business intelligence strategies.
The premise of both the white paper and the presentation is that the key to success in business is effective decisions. This is not a ground-breaking suggestion – after all no one would argue that it really is the decisions that companies make that lead to improved organizational performance. In fact, an interesting and relevant study done in 2007 by SAS titled Business Intelligence Maturity and the Quest for Better Performance showed how a company’s maturity with their BI strategies and their use of information analytics can directly impact organizational performance and company growth over time. This study concludes that “organizations that are further along in the areas of advanced analytics, information access technology and cross-organizational data integration seem to be achieving a higher level of performance.”
But, while the data exists that shows the benefits and opportunities that exist in the context of BI, there is also still plenty instances where BI strategies fail within organizations or fail to improve an organization’s ability to make effective decisions. In a 2009 study, Gartner predicted that “more than 35% of the top 5,000 global companies will regularly fail to make insightful decisions about significant changes in their business and markets.”
So, it would seem that there are contradicting circumstances out there in that the proof for the benefit of BI strategies within business is abundant, but companies are still commonly failing when it comes to turning business intelligence into effective decision-making.
I think to identify the reason behind this condition, we need to go back to the origins of BI way back in the early 1960s when a concept called Decision Support Systems (DSS) gained popularity. DSS was a discipline for modeling data to predict and analyze performance within businesses and gave birth to the business intelligence concept that we know today. Over the past 4 decades, BI has evolved into a well-established technology based discipline and has permeated many industries. While at first popular in retail and financial services, BI has expanded to most industries including the professional services industry in which architecture and engineering firms reside.
This expansion and evolution, I feel, has led to a bit of a commoditization of BI concepts and the technologies that support BI systems. As a result, BI strategies are too narrowly focused on data. I think it is common to think first of data, reports, information, charts, graphs, etc. when discussing BI. But, what seems to have gotten lost is the fact that what an organization does with that data or information is what can actually lead to improved performance…not the data itself. The discipline of BI needs to get back to its roots which can be found in the definition of BI provided by Hans Peter Luhn, the IBM researcher typically credited with originally coining the term “business intelligence”. Luhn defines BI as “the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal”. It is the component of “guiding action towards a desired goal” that seems to often get lost amongst data-centric considerations for BI strategies.
What all organizations need to understand is that a successful BI strategy needs to be a part of a feedback loop. A feedback loop is a profoundly effective tool for improving performance. The concept is simple – measure performance, make that measurement relevant my comparing it against a goal, react to how the measurement stacks up to the goal and identify resulting choices and then take some action that will presumably get the organization closer to achieving the goal. Then, start the process all over again…creating a cycle that is constantly aimed at improving performance. It is the cyclical nature of a feedback loop that can make it so effective. If organizations embrace feedback loops as a part of their operational process they can become cultural and somewhat self-fulfilling by fostering good habits around decision making. Without a feedback loop, a BI strategy is just dumb data or technology for technology’s sake.
In talking with Deltek customers and leaning on industry expertise from ZweigWhite, we were able to identify several best practices around BI strategies and integral feedback loops. These best practices can help firms exploit the opportunities BI has to offer. Below is a list of those best practices along with a brief description of each.
- Communication – when it comes to communication and business intelligence, it is not just about talking about BI. Instead, it is about transparency and visibility. Organizations must “share the numbers” and advertise why decisions are made. This will not only make what is important to the organization very clear to everyone in but it will also create a common vocabulary and highlight what organizational behaviors need to be modified to enable the company to reach its goals.
- Goals – many organizations have a component of BI in place in their organization by providing measurements on performance. However, unless goals are established those measurements are irrelevant. Organizations must establish goals so that what success looks like is clear to the entire enterprise. Without goals it is nearly impossible to implement an effective feedback loop.
- Demonstrate the Value – often times BI strategies within an organization get the stigma of just another piece of technology for technology’s sake. Or, BI is perceived as stacks and stacks of reports and data. However, by demonstrating how a systemized use of BI is actually positively effecting organizational performance, these faulty perceptions can be avoided. A little internal PR can go a long way in selling the value of a BI system – when a BI strategy leads to improvement in performance organizations should advertise it; when an organization is not achieving a goal they have set, what steps are being taken to turn things around should be advertised as well.
- Business Fundamentals – organizations should never assume that consumers of organizational performance data have a complete understanding of what they are seeing. Organizations may find significant value in investing in some business fundamentals or accounting education for their staff. Perhaps an “Accounting 101” session available to all staff. This will help ensure that everyone understands the terms and concepts that relate to organizational performance.
- Leverage Business Intelligence Software – companies must allow the BI software that they have chosen to do the heavy lifting. For BI strategies to be effective, organizations must avoid getting stuck in the quagmire of spreadsheets or allowing different units within the organization to use different ways and different tools to consume performance data. By allowing the purpose-built BI software to be the single facilitator for BI consumption and analysis, everyone will be looking at the same data in the same way which will enable a greater focus on decision making.
- Success Requires Commitment – like any strategic initiative the use of BI within an organization requires a commitment for it to be successful. Success with BI is not going to happen overnight and it will take effort. The best way to get started is to start small and let the use of BI evolve over time. By allowing it to evolve and works its way into the operations of a company it will become somewhat cultural and therefore a self-fulfilling condition.
Every firm is different in regards to maturity level and culture. As a result, implementation of successful BI strategies will be different for each company. However, by keeping these best practices in mind and focusing your strategy around feedback loops, the true value of BI can be realized and you too can improve your organizational performance.
In sharing this presentation with the AIA Large Firm User Group, there was consensus amongst the audience that mature use of information analytics and deliberate BI strategies are an important part of a an organization’s operations. In addition, the audience could relate to the best practices that were presented and understood how those best practices could help make BI strategies within their companies more “sticky” and more successful.
However, the audience was also keenly interested in what Deltek was doing with Vision to better-align it with these best practices and how Vision could help companies achieve successfully BI implementations that would then lead to more effective decision making. This is a fair question and I had a lot to share in regards to the BI stack within Vision. With the next release of Vision (Vision 7.0), the Vision Performance Management (VPM) module will be enhanced significantly further improving and enabling the measurement and goal component of the feedback loop within companies. In addition, some core improvements in Vision 7 will also help with organizations awareness and consumption of information.
I shared with the audience the following improvements, to which they can look forward, in the 7.0 release of Vision.
- Goals and KPIs – the VPM module will provide the ability to configure goals and key performance indicators (KPI) directly within the Vision system. With these goals and KPIs in place, the VPM performance dashboards can include both actual performance data and compare that data to the established goals and KPIs. This will allow for a very quick interpretation of where the organization stands in regards to a specific measurement. These goals and KPIs will be able to be established at multiple levels of granularity from company-wide goals, to business unit goals down to employee specific goals.
- Predictive Analysis – the VPM module in Vision 7.0 includes a massive expansion of the measures that are available for analysis. As a result, analysis can be done that includes both historical, current and predictive measures. For example, Project Planning data will be included within the VPM dataset enabling forward-looking analysis on things like planned labor and planned revenue. In addition, data around CRM components of the Vision system, like Opportunities and Activities, will also be included creating the ability for broader predictive analysis.
- Role Focused – the VPM module in Vision 7.0 includes an expansion of the role focused performance dashboards. This approach to consumption of the data that VPM provides is important because while BI is really relevant for everyone, each role requires different types of data and can benefit from different presentation methods for that data. With Vision 7.0, performance dashboards have been added for two new roles – Business Development Manager and Resource Manager.
I also shared some information on efforts beyond Vision 7.0. Specifically, the fact that Deltek is continuing to look at other ways to further expand the value and effectiveness of Vision’s BI stack. Sharing this information with the audience about future Vision BI capabilities generated a lively discussion and reaffirmed that Deltek has the right focus in regards to where it is going with the VPM module.
In addition, it was clear that the group did feel that the implementation of BI strategies can have a definitive positive impact on organizational performance. No doubt there are definitely challenges out there when it comes to getting BI strategies to “stick” within organizations. But, by recognizing the opportunity a good systemized use of BI can create, understanding the importance of a feedback loop and considering the best practices presented to the CFOs of the AIA Large Firm Roundtable, organizations can enable more effective decision making which can lead to improved organizational performance.