Assess your analytics maturity against your peers with DEEM™

Cloud analytics is an excellent way to process large quantities of data and generate actionable, quality-driven insights. The cloud is the ideal platform for analytics, thanks to lower costs and virtually infinite scalability when compared to on-premises. While this combination of cloud platforms and analytics processes is proven to generate significant value, the benefits only fully manifest when an enterprise uses the technology to its fullest potential.

A powerful method for determining performance in the IT industry is benchmarking: the quantitative and qualitative assessment of platforms and systems to gauge performance against similar platforms and systems. A well-designed testing methodology can be leveraged to benchmark analytics on cloud, determining whether your cloud analytics solution perform is on-par, below, or above similar enterprises in your industry.

For this specific purpose, Trianz created the Digital Enterprise Evolution Model™, or DEEM. It allows Trianz consultants to quickly determine the cloud analytics maturity of clients, effectively guiding the next steps in an enterprise's digital transformation.

DEEM Stages

Let us briefly explore the five maturity levels of the Digital Enterprise Evolution Model™.

Level 1

At this level, enterprises are predominantly using manual processes—with little or no automation. This may include tracking data in Excel spreadsheets, with system reporting managed manually via email notifications or within helpdesk software. An enterprise at this level is likely to be more reactive than proactive and lacks widespread digitalization of data processes and procedures.

~30% of enterprises have only reached this level of maturity.

Level 2

At level 2, enterprises are taking steps to manage their data more effectively. Enterprises may have a cloud data warehousing solution in place, with master data management (MDM) to enforce data governance policies at the edge of their network. For level 2 enterprises, reporting is usually conducted on an ad-hoc basis, with custom reporting metrics being used in specific circumstances but not holistically.

~30% of enterprises are at this level of maturity.

Level 3

At level 3, enterprises are using more targeted and specialized tools to control and analyze data. A level 3 enterprise may use business intelligence (BI) reporting dashboards to visualize data, with trend or forecasting analytics to enable a more proactive approach. Enterprises may leverage public data, big data and even social data to generate more analytics insight, storing these large quantities of data in a cloud data lake.

~20% of companies have maturity at this level.

Level 4

At level 4, enterprises will use a combination of predictive and prescriptive analytics to guide business decisions, avoiding dependency on the perspective of the highest-paid person's opinion (HiPPO). Data-driven insights are increasingly relied upon to justify decision-making processes across the business. Humans still make the final decisions after assessing this insight, with some use of automation or artificial intelligence (AI) and machine learning (ML).

~15% of companies have maturity at this level

Level 5

At level 5, enterprises fully leverage their data to generate insights that enable the automation of systems and processes—specifically through artificial intelligence and machine learning. The hands-off approach can result in self-healing IT infrastructure, automated reports, and alerts for key stakeholders, as well as long-term forecasting with enhanced levels of accuracy.

~5% of enterprises have maturity at this level.

Using DEEM™ to Benchmark Cloud Analytics

The Digital Enterprise Evolution Model™ uses data-driven insights related to industry competitors and technologies used to benchmark your enterprise's cloud analytics maturity. With DEEM™, the subject pool consists of more than 40,000 companies across 18+ industries worldwide.

By realistically determining your enterprise DEEM™ level, the model can help enterprises identify gaps in their processes and technologies. The data will present clear pathways for digital transformation initiatives—highlighting both strong and weak areas for a targeted and transformative approach.

DEEM™ is suitable for benchmarking enterprise IT capabilities in the following areas:

• Enterprise Data Strategy – Better define your vision or roadmap for enterprise data usage, including data storage, data transfer, and analytics.
• Data Governance – Defining appropriate access to data by users, services, and systems. Leading to remediation of improper data access patterns and controls.
• Master Data Management (MDM) – Improve process of upholding uniformity, accuracy, access control, consistency, and accountability with primary datasets used by the business.
• Data Quality Management (DQM) – Create a pipeline-driven process of validating data quality during ingestion into a data warehouse or data lake.
• AI Capabilities – An assessment of artificial intelligence capabilities surrounding data storage and data analytics.
• Investment Models and Priorities – A framework for investing in new technologies and systems, with prioritization weighted against the DEEM™ model.
• Data Analytics and Organizational Structures – A measure of how analytics is utilized across the organization – including analytics stewardship, knowledge sharing, and data reliance.

• Analytics Technologies – An assessment of the technical capabilities of existing analytics technologies against best-in-class products and services. 

• Cyber Security – A grading of data security – including data security frameworks, encryption utilization, access controls, and more – against cyber security leaders.

Make the Right Cloud Analytics Investment with DEEM™

According to our sister research firm Trasers, data visualization is the most leveraged technology by digital champions—with 83% of decision-makers adopting it. This is closely followed by the Internet of Things (IoT) with 80% adoption, and social listening/social analytics at 77% adoption.

DEEM™ will help you identify shortcomings in your existing cloud analytics solution or framework, and create a plan of action to transform your analytics capabilities. By starting with areas that provide maximum impact, your enterprise can significantly improve its competitiveness within your industry.

You can read more about DEEM™ and Trianz' benchmarking capabilities on Trianz.com.

Author: Paul Brunda, Benchmarking Practice Leader, Trianz

Paul Brunda is an operations technology leader and a change agent. With close to 30 years of experience working with big names on Wall Street to healthcare and insurance, Paul has unique insights into the areas of cloud, security, platform, and compliance systems. He advises clients to benefit from growing digitalization by leveraging the cloud. His key specialization includes engineering issues, operational security, and compliance controls.