Rising SI and Consultant Use on BI Projects Means Data Leaders
Must Provide the Data and Analytics Guardrails

Our latest data show that use and perceived importance of system integrators (SIs) and consultants continues to rise. Organizations increasingly allocate greater percentages of their data and analytics project budgets to the use of SIs and consultants.

In addition, expertise matters most when choosing an SI or consultant. And when sourcing that talent, organizations increasingly consider their vendors as trusted advisors that can direct them to the right potential SI and consultant resources to use.

As perceptions, use, and funding of SIs and consultants continue to rise, so do the stakes for data leaders. Hiring SIs and consultants for an increasing percentage of project responsibilities requires greater expertise in managing the engagements. In some cases, an engagement manager can handle more projects—as long as other less-critical workloads and responsibilities get offloaded easily and efficiently. Sometimes a data leader simply will have to make a business case for hiring more engagement managers. But in almost no instances—even for the most critical projects—should a data leader look to manage these engagements directly.

The reason: SI and consultant engagements most frequently tend to be “in the weeds”—mainly application / solutions development and technical consulting, followed closely by staff augmentation. Quite simply, a data leader dedicating significant time to direct oversight of SI and consultant engagements is not prioritizing her or his time properly, and is shortchanging the organization in the longer term for two reasons.

First, a data leader can and should lead the organization in the most effective and efficient use and leverage of data to improve decision making and better enable processes and operations. Micromanaging implementation projects, for example, does little if anything to assist with that greater mission. Second, people working for the data leader need to develop skills for managing SI and consultant engagements. The data show that use of SIs and consultants will likely increase in your organization. Therefore, the data leader that tries to manage these engagements directly—instead of delegating to qualified staff—increases risk that the organization will not have developed sufficient skills among existing staff to manage for future growth in use of SIs and consultants.

Instead, a data leader should coordinate as needed with project managers but still primarily focus on influencing the foundations for and use of data and analytics throughout the organization. These data and analytics “guardrails” include data governance principles and programs; data management initiatives such as data integration, data quality, and master data management; guidance on where and when certain analytical techniques are appropriate and which data sources to use; as well as strategies regarding data availability and use in generative AI.

Such prioritization make sense for a data leader—staff handles the granular detail of managing specific (often technically oriented) engagements while the data leader guides proper focus on the principles of Hyper-Decisiveness while ensuring initiatives improve the Hyper-Decisive® maturity of the organization.

Beyond tracking SI and consultant engagements at the highest level, a data leader also needs to check and validate the reasons why the organization uses SIs and consultants. The drivers can vary—such as providing industry expertise, adding temporary staff when business conditions preclude permanent hires, or supplying detailed technical skills. Some organizations frequently use SIs and consultants because processes and procedures make it easier and faster to engage with SIs and consultants than it is to justify and approve hiring permanent staff for similar roles.

Business conditions and the factors that drove previous decisions to use SIs and consultants change. A data leader needs to revisit those choices made in the context of these changes and then validate or alter how to proceed with future engagements.

For example, if specific technical skills previously and currently provided by an SI or consultant have become mission critical to the organization, the data leader may need to advance the case for establishing and building those skills in house, rather than always look to an external provider. Also, for example, failing to identify a business driver other than “that’s how we’ve always done this” should serve as a red flag that alignment between need and approach requires further review and analysis. In such an instance, continuation of the status quo could increase risk of misalignment with other strategic plans and business needs. Having such regular reviews of SI and consultant use for alignment with strategy and business goals and needs will help ensure an organization keeps the right balance between gaining economic efficiency and having its required capabilities.

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