As tools change, so do professions – just ask the retired typesetter, switchboard operator, or milkman. And with digitalization, professional services companies are changing rapidly, from top down and bottom up. How firms engage with customers, conceive of solutions to meet customer needs, and provide services and expertise to get the job done are all increasingly driven by digital solutions and, fundamentally, by data.
Recently, data tools have gone through their own transformation, and these changes impact every professional services company that aims to survive and prosper. Your data analysts already know the benefits of analytics – automating repetitive tasks, reducing costs, enhancing the customer experience, and so on. But accessing and using data from across and outside of an enterprise – data of diverse types and from different sources – to perform analytics on a grand scale for multiple use cases – was easier said than done. Until now.
Based on our global experience of working with the leading, most innovative professional services companies, here are three SAP “next practices” – capabilities and outcomes to help companies utilize data and analytics on a much grander scale.
Integrate diverse data sources. Data is scattered. It’s in multiple applications, files, data warehouses, data lakes, and public and private clouds. Each silo walls off the data with proprietary rules and complexity. You need visibility into that data. Without it, you have an incomplete picture of the business. With it, you can gain real-time visibility into actual-to-forecast project cost. You can perform customer sentiment analysis, combining diverse unstructured and structured data sources (e.g., stock prices, social media) to guide strategy. And much, much more.
Next practice #1: Integrate your data by combining datasets – including Big Data, process data, product data, analytical data, etc. – as needed into a single data universe for much greater visibility.
Next practice #2: Integrate your data sources, using orchestration and governance solutions. Go from raw feed to intelligence with real-time analysis of vast data sets. How? With solutions to understand, integrate, cleanse, manage, associate, and archive data to optimize business processes and analytical insights.
Simplify your data landscape. Centralized. Easy-to-use. Automated. That’s what you want from your data analytics platform. And those features have been a challenge because of all the different databases, apps, and clouds in your IT and business environment. But now a centralized data management solution is available that manages all facets of a professional services firm’s data universe. Represented visually, the architecture is easy to share and understand. Stakeholders assigned to an architecture team within your company can collaborate through a user-friendly Web application in the planning, design, and governance of the architecture.
Next practice #3: Create and maintain a complete landscape architecture that is easy to share and understand. Open up this landscape to an array of company employees and managers to jointly manage your data environment as an agile, strategic tool.
A growing number of data analytics use cases for professional services companies
Data analytics is being recognized as a vital tool for professional services companies that need to innovate faster than the competition, create new markets and services quickly, automate processes, and attract and retain customers. The need for speed has grown – along with the diverse types and quantity of data. Becoming a truly intelligent professional services company requires a reliable, easy-to-use platform to capture, ingest, process, orchestrate, compute, and consume data at tremendous scale.
SAP customers in professional services that are intelligent enterprises are using data analytics fed by an increasing array of data sets for use cases that include:
- Bid management to analyze historical bid information for skill and staffing requirements and pricing
- Project management and governance to create an integrated view of project portfolios with a changelog, documentation, and third-party access
- Customer sentiment analysis using predefined exploration views and dashboards to keep up with customer trends
- Total margin management with analysis of detailed customer profitability data to identify and predict revenue leakage and fraud
These are just some of the many quickly evolving, creative ways that larger and diverse datasets are being put to work by intelligent professional services companies today. Some use cases are relevant to every type of organization within the industry. Others are more suited to different types of businesses, geographies, markets, and other unique characteristics.
For more on how professional services companies around the world are transforming into intelligent enterprises, read the new SAP white paper “The Data-Driven Professional Services Company – Data Management for the Intelligent Enterprise.”
And please listen to the replay of our “Pathways to the Intelligent Enterprise” Webinar, featuring Phil Carter, chief analyst at IDC, and SAP’s Dan Kearnan and Ginger Gatling.