How to Control the Proliferation of Your Data Tools

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Technology and data leaders (CIOs in particular) struggle to gain control of the ever-growing technology platforms that they are expected to support. We have some advice on how to streamline toolsets for better data management, more insightful analytics, and even cost savings.

Most companies face this situation: the number of tools and technology used across the organization continues to grow, but departments work in silos using tools that overlap in function or are not compatible with each other. Siloed tools and systems can present many challenges for a business, including overly complex environments, redundant and inefficient processes, lack of one version of truth, segmented view of performance, no trust in the data, low user adoption, and more.

How to Control the Proliferation of Toolsets

Here are some tips to reduce your number of toolsets and keep user frustrations at a minimum during the process.

  1. Take inventory of all tools used by the organization– Start off by making a list of all the tools that are used at the organization, what they are used for, who they are used by, etc. This may require you to interview various business stakeholders from all departments. At this point, you can identify where differing tools are being used for the same purpose or which tools are barely utilized.  It’s not uncommon for companies to realize they are using tools no longer supported by a vendor or that analysts are performing certain data manipulation processes on and old custom app that poses security threats.
  2. Note tool inter-dependencies – What is each tool being sourced from or providing information to? If a tool is eventually considered for elimination, it’s important to know all the other tools that could be impacted. We recommend completing an impact analysis chart that lists out the inter-dependencies between all the technologies that were inventoried.
  3. Complete a Tool Evaluation Identify the pros and cons of each tool relative to the business needs. This assessment should be done keeping the organizations strategic short term and long-term goals in mind. For example, one of our customers completed an inventory of data warehousing solutions and found that three different tools were being used for essentially the same work (Amazon Redshift, Teradata and SAP Rapid marts). The pros/cons analysis of setup, manageability, scalability, and pricing helped the customer make an educated decision on which solution best met their organizational needs while eliminating tool bloat and reducing technology expenses.
  4. Assess skillsets – If consolidating tools means a lot of users need training on a new tool, what are the costs associated with that? Evaluate skillsets across the organization to determine which tools match current skillsets and where the gaps exist. Skillset was a major factor when performing the Tool Evaluation exercise with our customer seeking out the best data warehouse solution. Since most of their workloads and applications were already hosted on AWS cloud, and the majority of their technical teams were well versed in AWS services, Amazon Redshift presented the lowest learning curve.
  5. Develop a training plan – Consolidation of tools means that some users must stop using a tool they’re comfortable with and start using something new and foreign. Before introducing tools and technology to new users, have comprehensive documentation and onboarding instructions in place. Provide more in-depth training for those who need it. When our customer chose Amazon Redshift as their data warehouse solution, we supplemented existing Redshift training documentation with customized instructions that accounted for specific business needs and operations. The resulting comprehensive documentation eased new users into using the new tool.
  6. Adopt a phased approach – Take a small-scale approach when introducing tools to new users. Start with a small number of users or test accounts rather than rolling out the changes to the entire organization at once. When we helped our customer downsize to a single data warehouse solution, we first introduced the tool to the teams who would experience the least disruption – those who had no application dependencies or no data warehouse already in place. Teams who had to switch data warehouse solutions (which had downstream effects on other applications) were saved for later phases of the migration as to learn from prior phases and minimize disturbances as much as possible.
  7. Continue to consolidate – Simplifying technologies and tools is an ongoing process. A good feedback loop is very important; each time you consolidate, learn from the process and take note of how to make the integration process smoother for any future consolidations. Cleanup also provides the opportunity to uncover operational improvements that could make day-to-day work easier, including simple initiatives like software updates or the purchase of new product licenses.
  8. Celebrate success along the way – Take note of “wins” along the way, such as dollars saved on licensing, hours saved by tool automation, better use of employees’ skill sets, and better alignment of department goals with the company’s overall data strategy. These wins should be leveraged to promote continued consolidation efforts.

Ready to streamline your tools and technology?

Tool consolidation is a challenging process, but with the appropriate planning, organizations can reap many benefits from operating on a more unified toolset. We can help you assess your current state, determine which tools best meet your business needs, and create a plan to consolidate your technology.

Neha Dixit is a Senior Consultant at Analytics8 with expertise in building data warehousing and BI solutions for customers across various verticals. She is an avid fan of superhero movies and enjoys exploring new restaurants and coffee shops.

 

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