In this article, we outline the role and importance of data for professional services firms. We discuss common data questions and the typical status quo of data management today. Lastly, we provide guidance on how to shape your firm’s individual data management capabilities to deliver on the promises of Big Data, Machine Learning, and Artificial Intelligence.

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How to increase the profitability of your firm by managing your data?

As professional services firms (PSF) respond to clients demanding more tangible solutions, consultants, tax advisors, auditors, lawyers, and marketing agencies are experimenting with the next generation of business models. We see professional services pushing into “everything-as-a-service” and generally much more “digital” approaches to delivering client value. These developments have sparked a renewed and even greater appetite for data than ever before - and not just their clients’ data, but their very own data: A discipline which has often been neglected and is mastered only by few players. We believe that next generation success models in professional services will be significantly determined by a firm’s ability to generate and leverage data in order to use analytics and artificial intelligence to drive insights, actions, and value for clients.

The problem: Many PSFs are only used to working on and with their clients’ data - to some extent. We can observe growing regulations around this topic in many countries and increasing awareness of these traditional data needs within the firms themselves. Nonetheless, there is still an almost universal lack of robust data architecture and management around most client data processes, sources, and pools. Even more dramatic and frequent is the vast neglect of the core and alternative data sources of PSFs themselves. Here are just some examples of questions, for which most firms would severely struggle to find the answer - let alone the data:

• Data on services, products, solutions: What does the firm exactly sell to clients? How well are their services/solutions doing across clients (e.g., in terms of profitability)? Which versions and variations are being delivered? So basically, all descriptions, definitions, master data, etc. that paint a meaningful picture of their business down to client-relevant deliverable levels.

• Data on value chains, delivery processes, and resources: How are services, products, and solutions being delivered? How well are delivery processes performing? Which deliverables are created at what costs? What is the actual price per deliverable and the entire solution? Which elements are standardized, repeatable across clients, and where does customization set in? Which methods, insights, and tools are being used? All these data points are often not collected in a systematic approach across all client engagements. But they are crucial as the next generation of business models goes mainstream, and more complex value chains cry for systematic and reliable management.

• Data on client journeys and sales channels: How and through which channels are clients interacting with the firm? What does the customer journey for certain clients or typical issues look like? How well do services, products, and solutions sell in which channels? How to best optimize channel usage and orchestration?

These questions may be asked occasionally but cannot be answered repeatedly or systematically for most PSFs - still, one might say. Finding answers has been left to the domains of knowledge management approaches or CRM efforts, which mostly share one trait: They fall short of their expectations and represent administrative hurdles instead of value generators for the business.

Only about 20% of professional and B2B service firms feel to have very effective enterprise-wide data management, according to KPMG’s CIO survey for 2019. The traditionally fuzzy nature and artisan guild thinking of professional services are probably one of the explanations for these underlying challenges. Moving away from “keeping people utilized” towards “reliably delivering clearly defined solutions” requires a major shift in strategic thinking on the management levels. And, we can now witness this paradigm shift for professional services taking shape: Technology spend is increasing dramatically. It is driven by the search for technology-driven and innovative growth, including new business models. Again, KPMG’s recent survey confirms these developments, which in turn drive precisely the above-mentioned questions (see also “Strategy For and With AI” by David Kiron and  Michael Schrage). In order to find answers, data is becoming the key ingredient for the next generation management playbook in legal, consulting, tax and accounting services.

PSF leaders are beginning to realize that the “battle for data” is on to deliver on the promises of Big Data, Machine Learning, Artificial Intelligence, and especially new and digital business models. But only 23% of PSFs are satisfied with their data-to-value conversion. Ramping up the data-to-value conversion is a crucial differentiator in the battle for data strategy acceptance. It will drive more rigorous business architecture, data models, and ultimately more holistic management efforts in general to professional services. Something that may be long overdue for several reasons.

So, we encourage PSFs to do at least four things to shape their data game right now:

1 Envision and define data-driven client solutions and delivery improvements. Infuse your strategic thinking with an explicit data dimension. Watch out for similar patterns in other industries. Once you have identified interesting use cases, work back towards the right data sources and supply chains for each case. Please do not treat this as a onetime exercise: Make it part of your strategy discussions, leadership, and management meetings across the firm. Repeatedly! Identify the right visionaries and evangelists within different areas of your firm to inspire action and keep momentum.

2 Create overarching data management responsibility, but also awareness and a sense of purpose and ownership across the firm. Take your key players on the data journey and create measures of success for “their” data elements to the big picture. Work actively with the different groups of data creators, processing units, and beneficiaries across the firm to realize specific and tangible use cases and, thus, success stories. Do not forget to celebrate success with everyone involved.

3 Pool your data & analytics competencies in one place or a virtual organization. The right talent, like data scientists, business and information architects, etc., are still scarce in many firms. Putting them within each business unit or assigning them to just single services or use cases is like “butter on too much bread.” Pool your talent and work across all business units, services, products, and solutions with a strategically prioritized view on the potential for success and your firm’s learning curve.

4 Identify the right partners to shape and execute your data strategy. This requires an honest assessment of your own capabilities - something that may be hard to swallow for larger PSFs,  who claim “to have all capabilities for their clients’ digital transformation.” But this game is not about advising yourself, but relentless execution and mastering digital business operations. Find the right technology partners and talents, who have played this game before. Systematically designing and shaping your digital business architecture for data sources, collection, and usage across the firm is becoming a key capability in professional services - and necessary in order to unlock the promises of artificial intelligence. The potential buried in PSFs’ data treasures is sheer limitless. PSFs that manage to capture, cleanse, store and process data systematically will not only set themselves apart from their immediate competition but also lay the basis for sustained future growth. Data-driven services and solutions will more accurately address client issues as they arise. A data-powered salesforce of professionals will be able to sell the most suitable services and solutions to the right client. More data-driven and transparent delivery will help to deliver results in a reliable and controlled process – and drive clients’ confidence in the results and their satisfaction.

This capability may determine success or failure for the next generation of business models. Especially in a professional services context, this thinking and capability must power strategic analyses and decisions, drive internal optimization, and, at the same time focus on the essence of delivering value the right way, at the right place and time for clients.

In order to live up to the demand for its services, a mid-sized professional services firm, realized that they could not hire new employees fast enough while maintaining the quality of their consulting services. So, they asked us to evaluate the potential for modularization, standardization, automation, and shared services delivery. Jointly, we quickly realized the key ingredient to successfully applying these levers for scalability and better profitability: Data – and better data management capabilities. After evaluating the firm’s service portfolio and strategic ambition, we defined three workstreams for a 2-year roadmap:

1. Data Landscape: Infusing key business activities with data capturing mechanisms (e.g., more precise and standardized descriptions of services, project activities and deliverables, which can be used in processes, file tagging, etc.). The aim was to minimize the required immediate investment needs while maximizing benefits through smart and mostly automated data generation, capturing, and leverage.

2. Data Management: Setting up data management capabilities and clear roles and responsibilities throughout the firm. It was critical to include as many people as possible on this journey. Use cases in the interest of all key groups and roles throughout the firm were jointly designed and defined – and communicated.

3. Data-driven Delivery Performance: To quickly harvest first benefits for the firm and communicate success stories, we selected two top-selling services and solutions for piloting the re-designed and now data-driven delivery and knowledge management processes. 

Conclusion

The results after about a year showed a significant improvement in terms of delivery performance (e.g., lower schedule and budget deviations) and higher profitability (between 6% and 11%) across all client engagements of the two selected services. But most importantly, professionals across the firm and on all levels were excited to have better visibility of available knowledge and insights for their client conversations and work.