A 2018 survey of ours found that 64% of respondents from companies with more than 10% growth in the past three years “strongly agree their organization is highly adept at leveraging data for insights, predictive outcomes, and business growth."
Companies need strong data insights to help them look beyond conventional cost reduction and automation to pinpoint the true drivers of productivity. Data enables executives to take a fresh, objective look at their managers. It allows them to see areas of the business that are building value and those that are creating waste. It reveals whether technology is enabling or hindering the processes it is supposed to be supporting. This data-driven performance management is the linchpin of profitable, high-growth businesses.
Many organizations struggle to get value from their analytics. They may be overwhelmed by the quantity of unstructured and disparate data they collect, or they may lack trust in the insights they receive, sometimes deriving different answers to the same question based on different data sets. Company silos may prevent insight sharing or interdepartmental analysis, and insights might be understood differently by different tribes within the company.
Most companies realize they need improved reporting and analytics. However, fears of time, cost, and previously failed attempts act as deterrents. Business units often fail to get the platform they need and wind up creating shadow IT systems that are laborious to maintain and deliver fragmented, low-value solutions.
Conventional approaches to data analytics such as spreadsheets relying on manual data extracts do not meet the dynamic, real-time needs of today’s rapidly evolving businesses. These approaches are slow and inflexible, requiring weeks or even months of painstaking and tedious planning.
Execution is cumbersome and gets bogged down in myriad data issues: Data arrives late, it gets stuck in legacy systems that don’t talk to one another, and it requires time-consuming manual cleanup. The project takes longer and puts a higher-than-expected burden on IT resources.
Companies that pursue such conventional methods tend to face new challenges when their systems are finally completed. They struggle to make sense of their data or realize they haven’t asked the right questions: The insights they thought they wanted are not the ones they really needed. Alternatively, the insights they receive lead them to realize new ones they could benefit from but are undeliverable because the platform is too rigid. Oftentimes the business has moved on by the time the system is completed, raising new questions or rendering the insights obsolete upon arrival.
The result? Companies that deploy such systems don’t manage to effectively harness insights from their data and, thus, can’t effectively compete.
To overcome these challenges, West Monroe uses a proprietary “Rapid Insights” solution. Rapid Insights enables any business — regardless of their data maturity level — to harness fresh, relevant insights in just weeks. Its speed and versatility make it particularly valuable for new acquisitions and private equity entities comprised of diverse businesses. If done well, this can be accomplished in six to eight weeks, four times faster than traditional approaches.
Rapid Insights uses an agile approach to promptly compile data, deliver a proof-of-concept, and speed the build out of more comprehensive and relevant analytics infrastructure. It short-circuits the rigid, time-consuming aspects of the conventional approach.
It starts by producing preliminary data visualizations within six to eight weeks. This enables business leaders to quickly see a rough draft of the fresh insights available from their data and allows them to begin making behavioral changes. Alternatively, if the analytics are not on target with the organization’s needs, Rapid Insights allows the data architecture to be modified – hypotheses are verified or refuted before significant data modeling investments are made.
These analytics sprints are refined and repeated, delivering insights every step of the way until the analytics and data governance are optimized. But the process involves much more than static reporting. Just as data is compiled in nimble sprints, management information and data science are applied to quick behavioral experiments to see if they can produce value before they are operationalized. Because the process is incremental and continuously delivers results, organizations can quickly see value, generating momentum for the initiative over the long term.
The bottom line: Rapid Insights enables business people to see in real time the art of the possible from data insights. This builds better analytics faster.
In contrast to conventional platform development, Rapid Insights begins by defining use-case hypotheses, asking questions such as:
It then uses nimble and powerful contemporary apps (such as Python/R Power BI and Tableau) that can directly embed data from sources such as Excel, Salesforce, Dynamics, and flat files. This makes it easy to quickly consolidate information from different sources (enterprise resource planning, operational, excel/flat file, and even mainframe) into a single data model.
This preliminary visualization step helps the company understand the data they have and the insights they can derive. The company can then manipulate its data interactively and create intuitive visualizations that are easy to share and understand before embarking on platform development. In fact, the initial insights and visualizations arrive more quickly than they would take to even plan a conventional data project. With Rapid Insights, executives can begin making decisions before a conventional analytics project would even get off the ground.
Once the initial insights are obtained and priorities are established, the Rapid Insights solution helps the company shore up its technical foundation to deliver better quality data with the flexibility of a cloud-based data warehouse. We can expedite development of a data warehouse using a proprietary “data warehouse accelerator.
We use an agile approach to deliver rapid and relevant results. Since the company has already gained a better understanding of its data through earlier steps, building the data warehouse is simplified and expedited. Rather than migrating all the data to the warehouse (per the conventional approach, which typically takes 80% of the data scientists’ time), only the most relevant data sources go through this process, dramatically reducing wasted effort.
Rapid Insights generally requires only a brief engagement of a few months, after which the company is sufficiently trained to handle its own data-insight needs. The outcome is self-service analytics. Business units are empowered to derive insights from data — nimbly, powerfully and rapidly — with minimal demand on IT resources or need for IT expertise.
Rapid Insights is laser-focused on solving business problems, quickly demonstrating value, and rapidly iterating . The solution has been proven effective with a variety of clients (see case examples in sidebars) and offers numerous advantages.
One key attribute is that Rapid Insights is led by the business with IT support. It targets business questions and helps build bridges between business needs and IT capabilities. This diminishes the potential of a divide between the business unit and IT. By enabling the business function to maintain control, the Rapid Insights approach ensures that stakeholders are involved throughout the process instead of just at the beginning and end.
This is possible because the technology used in the early sprints is user-friendly for non-technologists. It is nimble and easily manipulated to demonstrate a variety of results. While the IT department is an integral partner in making the data available and ultimately managing the data warehouse, Rapid Insights allows managers to easily perform their own analytics.
Rapid Insights also significantly reduces the risk associated with analytics projects because it requires a smaller investment than conventional approaches. For most businesses, the biggest advantage of Rapid Insights is speed and flexibility. Because there is no upfront tech development, data insights arrive in weeks, creating immediate value.
The Rapid Insights approach works at the speed of modern business. This speed energizes stakeholders, increasing the stickiness of the analytics initiative.
Of course, to fully realize the benefits of contemporary analytics over the long term, organizations must improve data literacy, help people understand how to make better decisions with data, and maintain their analytics systems. Rapid Insights can jump-start the proficient data use that is so vital for growth and success in the marketplace. The approach makes it much easier to get started and dramatically boosts the likelihood that the organization will attain a strong return on their analytics investment.
Given the power, flexibility, and cost advantages of Rapid Insights, we advise companies to review their analytics needs to determine whether current approaches are effectively and efficiently delivering the insights they need at the necessary speed. If not, we encourage you to contact us to explore whether the Rapid Insights solution may be an appropriate alternative.
A leading optical retailer had been a data-driven company, but its evolving data requirements began to outpace IT teams’ ability to support them. As a result, business users began to work around IT by using Excel and Access databases, creating data silos across the organization. This led to complex, error-prone manual processes and point solutions that employed divergent business definitions and produced different versions of the truth.
We helped the client transform their business intelligence tools and processes through IT modernization and automation, technology implementation, and design and execution of training programs. The outcome was a fully operational automated business intelligence platform, operated by business units and supported by existing IT staff.
All parts of the organization – from executive leadership to business units to doctors and field associates to home-office functions – use one source for data and analytics while also having self-service capabilities for managing their specific reporting needs. The company-wide data solution is enabling effective decision making today, while providing the flexibility to add new data sources, key performance indicators, and reports as future needs evolve.
The outcome was a fully operational automated business intelligence platform, operated by business units and supported by existing IT staff.
After exploring its data using the Rapid Insights approach, we helped a mid-level insurance company develop a machine-learning algorithm that automatically recommended new products to renewing customers based on what similar customers had purchased. The company is now earning $20 million in additional revenue thanks to this innovation.
The company is now earning $20 million in additional revenue thanks to this innovation.
Immediately after a private equity firm purchased a leading global IT systems integrator, it sought to better understand the firm’s bookings, revenues, costs, and customer profitability.
Using Power BI and data from the company’s enterprise resource planning (ERP) application, we were able to quickly deliver reporting and analytics use cases, providing insights that executives needed in order to make strategic decisions. We then gathered feedback from the company’s business owners, iterated on the analytics and determined business analytics priorities. Based on this, we helped the company design and build a modern data platform to support the company’s future growth.
We helped the company design and build a modern data platform to support the company's future growth.
I am even more accessible than the other modals.