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Process Tempo Insights

  • Daria Chadwick

Seven Common Challenges When Fielding Internal Analytics Teams



Organizations attempting to field a dedicated internal analytics center of excellence face similar challenges - regardless of the industry they occupy.

The pandemic, increased global competitiveness, and the focus on digital transformation have all placed a great deal of pressure on data and analytics teams to rapidly deliver impactful insight.


Worldwide IT spending is projected to total $3.9 trillion in 2021, an increase of 6.2% from 2020, according to the latest forecast by Gartner, Inc. An increasingly larger portion of this spend going toward cloud-based applications and services.


While shifting dependency to the cloud is a sensible move, the elephant in the room is the stubborn presence of legacy systems and the complex web of processes and procedures that stand in the way. Internal analytics teams are forced to navigate this complex web in order to meet the demands of modern-day data-driven decision-making.


Internal analytics teams face seven common challenges centered around staffing, workloads, processes, and the enterprise’s existing set of tools.


The Seven Common Challenges of Fielding Internal Analytics Teams



1

Developing an internal team with a broad set of skills can be a very difficult, costly, and time-consuming process. World-class analysts are in high demand and the market is seeing an acute shortage of available talent. 60 percent of businesses believe it is harder to source talent for data and analytics positions than for any other roles. Even those with self-described "comprehensive" teams are unlikely to collectively accommodate the needs of the modern organization and rapidly changing requirements.

 

2

The constant and increasing demand for analytics-based insight generates a growing backlog of unmet deliverables. Internal teams are often unable to keep up with an increasing number of analytics requests and deadlines. It can take days, weeks, or even months to accommodate individual data requests. By the time reports are received, data can be outdated, in the incorrect format, or completely unusable.


 

3

Organizations and analytics teams have collectively adopted platforms that are capable of scaling data and data processing through services like AWS, Snowflake, Google Cloud, and the like - but have yet to find ways to scale the subject matter expertise required to produce insight and information.


 

4

Data and analytics architectures are littered with individual tools and platforms, creating a lack of cohesive architecture and causing an undue complexity that is incredibly difficult to navigate and manage.


 

5

Direct data pipelines complicate the issue in that they are individually complex, produced en masse for single requirements, and often have little to no reuse.


 

6

System-generated data often needs to be blended with people and process-based data to create contextual insight for decision-making. This means that relevant datasets need to be matched together. This matching or blending process is often a manual effort and continually proves difficult for many in-house teams.


 

7

Feedback mechanisms to improve data are not often implemented as part of a continuous improvement (CI) effort as current data architectures do not support this capability. This means both processes and teams aren't adapting and improving as they go - an unsustainable approach to take in modern data. With the rate that data complexity and volume is increasing, teams need to be constantly working to stay up to date with processes that can accelerate and not hinder productivity or data flows.



If you’re faced with any of these challenges with your internal analytics teams, it may be time to look into bringing on a Managed Analytics Service to help alleviate these difficulties and drive your business forward. Managed Analytics Services can help free up time, money, and resources for your internal analytics teams.


Learn more about how MAaaS can help:

 

Managed Analytics as a Service (MAaaS) from Process Tempo is an analytics solution that helps your entire team make intelligent and profitable decisions by leveraging your data - and all without a heavy, upfront investment. By choosing an efficient, fast, and cost-effective path to insights, we can help you beat your competitors in today’s data-driven, competitive digital economy. By adopting MAaaS, stakeholders can focus on achieving sustainable and predictable profitable growth.


Ready to get started with Managed Analytics? Read more about Process Tempo's Approach to Managed Analytics or schedule an introductory session. Process Tempo is a hybrid cloud, data management & analytics platform that breaks down silos to allow people, processes, and technologies to seamlessly work together. The platform supports a secure, governed, scalable, and high-performance environment for analysts and data scientists while serving as the foundation to deliver insights to all employees. It helps to deliver markedly fast, actionable, and accurate insights, easily incorporates a semantic data layer to curate and recommend information from across the organization, and makes every employee a first-class citizen in contributing insights and feedback to make the organization smarter over time.


Learn more about the platform here.


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