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Business Intelligence (BI) Roadmaps: Techniques for Utilizing Data Insights Effectively

Data insights are made possible by business intelligence (BI) roadmaps when the raw data they’re based upon is complete and accurate. That might sound a little obvious, but imagine how much information a medium-sized company produces. Huge amounts, and that quantity will only increase as more companies convert to data-driven economical models and modern data management systems. In short, technology creates mountains of virtual numbers. That data is a vital resource for informing corporation executives of incoming trends, but it’s not in an easy to interpret format.

So, how does that medium-sized organization utilize data insights? How does any company, big or small, effectively employ newly collected and analyzed data reports in a way that’ll benefit their bottom line?

Actionable Intelligence Based on Reliable Data

Nothing happens without a solid foundation. It’s up to company stakeholders to define this corporate baseline. They decide the productivity levels and profit margins, the marketing campaigns, and any other areas where improvements can be made. These Key Performance Indicators (KPIs) are identified and defined at this point, all the better to establish a reference point as progress commences.

To gain the best results, the collected data is complete, accurate and reliable, as defined by the assigned Chief Data Officer (CDO). It’s come in from a distant point of sales (PoS) system at a retail store, from a head office spreadsheet, an enterprise-level database, or maybe it’s been sent from a logistics executive within the supply chain department. To be truly complete, the numbers have funneled in from the most remote corners of the organization. But this is still raw information, not a refined set of BI ready data insights. Data analytics tools come to the forefront at this point in the process.

Conventional technologies apply statistical analysis methods here, the data is profiled and evaluated, analytics tools are applied, and the results are added as data insights to a Business Intelligence Roadmap. This is an established methodology, but it’s currently experiencing a paradigm shift.

Weighing Structured vs. Unstructured Data Collection Methodologies

If receipts are collected from a retail store, the raw data contained therein is processed, but the information is slow to integrate. That’s because it’s unstructured. On the other hand, taken directly from a database, structured fields are immediately recorded. Data insights are produced quickly when the information is laid out in a manner that computational systems can interpret, slowly when entered in a non-standard format.

One solution to this issue is for the CDO to commission a set of templates and standardized forms. If a customer survey is assigned using one of these templates, information can be easily recorded to a database. Then the information is computer collated and sent to the machine learning module. Optical readers could even be used to further accelerate the process.

Building A BI Roadmap: Leveraging The Human Factor

Continuing on from the conclusions in the previous section, preparation is key. Data should be cleaned and stored. For the latter concern, local or cloud storage options are available. Again, the CDO will be tasked with additional assignments. These could be as trivial as adding a security certification or as significant as adding a layer of encryption.

Focusing more on the Business Intelligence Roadmap itself, this is a visual company resource, one that’s attuned to the human eye. Live reports will be generated from the data. After all, the goal of this digitally tailored business strategy is to highlight trends and patterns, and there’s no better way to do this than with a data visualization platform. To incorporate this data insight emphasizing feature and leverage the full power of a visual roadmap, reports are created with charts. These can be used, for example, to inform company stakeholders of past supply chain deficits or to inform those same investors of future growth patterns based on current trends. Think about it, nothing helps a stakeholder grasp some abstract financial trend better than a PowerPoint graph generated by a cleverly utilized data insight.

Closing Thoughts On BI Roadmaps

A company thrives or fails based on a pivotal group of business indicators. These Key Performance Indicators (KPIs) are quantifiable metrics. In order for actionable insights to be clearly defined in a Business Intelligence Roadmap, those metrics should be positioned right at the center of the blueprint. They’re the only part of the strategy that won’t alter, not unless the CDO or their superior orders a change in a corporation’s fundamental workings. Everything else in the roadmap is in flux because the strategy is a living, breathing entity in its own right. As the data changes, so to does the generated data analytics.

Data insights, utilized effectively, inform stakeholders and executives. Used as the fuel and engine for visually attuned BI Roadmaps, strategies that are dynamic and always in motion, they tell organization executives exactly where they are and where they’re going so that strategic cost-saving strategies and edge-gaining corporate competiveness can be incorporated and adjusted on-the-fly at a moment’s notice.

About the author

Caitlyn Depp

Caitlyn is the Marketing Communications Manager at GrapeCity. She enjoys working with a creative team that is open to new ideas and learning about technology. In her spare time, Caitlyn enjoys reading, coloring, and going to the thrift store. Caitlyn has a Bachelor of Arts in Integrated Marketing Communications from Duquesne University. You can connect with Caitlyn via LinkedIn.

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