Autoservicio en la inteligencia de Negocios

Let´s to talk about Business Intelligence consultancy. This morning I spent some time reflecting on Business Intelligence, the current state of the market, and best practices; this thought process led me to consider the reason why some organizations are wildly successful with their BI initiatives and some deployments are catastrophic. The overall market has shifted these past five years or so—businesses large and small are moving away from multi-million dollar enterprise data warehousing projects to self-service BI initiatives led by different functional areas within each business.

Overall, every business I work with has different initiatives, priorities, and requirements. These varying needs make choosing one solution to fit all needs nearly impossible. Some business units require forecasting and basic reporting, others require visualizations to display trends and run statistical analyses. Others simply need their column and row reports to display transactional data to run day-to-day operations. While every requirement within the business reflects a need and potentially a specific, separate business case for that department, the challenge is finding a ‘one-size-fits-all’ product to fulfill these requirements. Through exhaustive searches, many businesses determine that the best product is one that fits their initial need and fulfills, to a lesser extent, some or all of their other requirements.

I find  that the most interesting component of this is that through self-service initiatives, with individual business areas purchasing tools to fit their highest priority needs, most organizations are able to achieve what they are looking for—matching requirements to products, with a multi-product reporting and analytics deployment. In some cases tools like Power BI may fulfill their needs, in other areas Tableau may provide the answer, others may require Excel or SQL Server Reporting Services; in all cases, the tools exist to meet these needs. Unfortunately, as most seasoned IT professionals know, when it comes to a successful Business Intelligence deployment, self-service solutions, and aligning products to requirements is only the tip of the iceberg for the organization.

The underlying challenge with what’s become a rapid shift from Enterprise Business Intelligence deployments to the far extreme of self-service, departmental BI, is the lack of an underlying, governed, data hub. Overall, organizations have solved their initial challenge of finding a tool that does exactly what they want and also provides easy access to the data. However, it also creates a significant problem for the entire business in terms of data reliability. Many organizations have latched onto fit-for-purpose tools as they attempt to move beyond easily manipulated data within platforms such as Excel to a strategy that ensures one version of the truth. Unfortunately, through self-service with open access to data, many tragically lose their way and end up with a nice tool and the hope that the data is meaningful and accurate. When these business units begin to rely on reports, dashboards, forecasts, and analytics without an underlying enterprise BI architecture supporting them, they are taking significant risks.

Being able to pull multiple source systems together, provide a unified view of the organizational data systems, and ensure the calculations and other blended-data are not being consolidated or manipulated in a way that only supports a single business area’s perspective, is paramount. The amount of access and flexibility these self-service tools provide is both exciting and frightening. As Gartner said just two months ago in Critical Capabilities for Business Intelligence and Analytics Platforms, “Through 2017, less than 40% of Self Service BI Initiatives will be governed sufficiently to prevent inconsistencies that adversely affect the business”. This risk eliminates the value of well-meaning and truly valuable self-service solutions and, should erode the business’ confidence in any of the data presented.

Providing a meaningful enterprise data intelligence solution through a unified data hub is the only way to eliminate this risk and drive the meaningful outcomes that today’s valuable self-service tools can provide. This is not to say that Enterprise business intelligence initiatives should still take place in their previous form, in fact, building a data warehouse manually in today’s technological landscape would be akin to Ford building their vehicles without the benefit of the assembly line.

The Business Intelligence consultancy firms of the world provide tremendous value to organizations needing skilled individuals to ensure processes are in place and the overall architecture provides what the business needs, as well as delivering meaningful enterprise and self-service capabilities. However, there are now tools which replace the manual build of data hubs to automate data blending with native, smart connections to business systems that are readily available and significantly de-risk these initiatives. The correct mix of a data intelligence solution, with a self-service BI solution (or many,) will provide the value, quick wins, and ability to effectively deploy trusted analytics and reporting tools throughout the business with pervasive adoption.
My reflection upon the state of the business intelligence market this morning is exciting based on my knowledge of my company’s product and direction; solidifying my overwhelming belief in the value of data intelligence and the value of a well-governed solution. Don’t get caught up in the data mess and problems that can arise from unfettered access to source systems and self-service data mashing within each business area. At this stage in the BI market’s lifecycle, the only true way to achieve success with business intelligence and confidently rely on your data is to ensure an automated, governed data hub is in place to support your data intelligence and business intelligence needs.

By Bill Tennant