Almost every management consultant can recall a time when manual slide creation was a significant part of their day-to-day work. In fact, it is quite common even for partners to spend late nights with their teams in the office, tweaking the graphs and revisiting spreadsheets to get the slides to look "just about right".
But modern BI and data analytics tools can become a game changer. Modern visualization technologies give you an opportunity to use real-time data analysis for faster and more powerful insights. This can transform the entire approach to solving client problems. While previously consultants would spend weeks collecting and manipulating static datasets, they can now build and run reusable data assets and interactive dashboards to unlock the power of clients' data for better decisions in hours.
This sentiment is echoed by Kirill Osipenko, a Product Manager at Google and former McKinsey Senior Product Manager, who has spent almost 10 years building enterprise software in the management consulting industry. Kirill understands the importance of leveraging modern data technologies to solve complex business problems and deliver value to clients faster.
Navigating the technology landscape and making the right tooling choice can be challenging for consulting firms with limited experience in the area of digital analytics. This article based on Kirill's expertise will explore common challenges and provide a roadmap for consulting teams to increase data literacy and accelerate technology advances for transformative client service.
Overcoming Roadblocks to Modernize Data Tooling in Consulting Companies
To successfully modernize data tooling, Kirill states that consulting companies need to address several common challenges that arise when product engineering teams are faced with consulting practices.
Data analytics should bring value, or it's worthless
Identifying specific opportunities for leveraging data in driving impact for clients is key to the successful adoption of new technologies in consulting companies. However, there can be multiple scenarios on solving client challenges with data tools, and deciding on the product vision can be a non-trivial problem.
It is crucial for consulting teams to recognize the fundamental differences between self-service data dashboards and curated data stories used for client presentations. Teams must identify the user persona early on and determine whether they aim to build a dashboard or a "storyline" tool, which can be integrated in consulting workflows. (If the team decides to develop a data dashboard, they may also consider granting clients direct access to this dashboard, which is yet another important product decision.) These scenarios should be discussed at the outset of any product development effort, so that both consulting and product engineering teams have full alignment on what problem is being solved and how the product intends to create value.
Consultants are used to their templates - and can miss out on opportunities
Most consulting teams have long-standing solutions, such as Excel and PowerPoint templates. When transitioning to modern data visualization tools, they often expect developers to preserve those existing templates and workflows in some form on the new platform. This approach can lead to missed opportunities, for example, to use interactive visualization techniques or otherwise leverage the new environment's unique capabilities.
Instead of trying to recreate the old scenarios with the new software, product teams should focus on addressing the underlying business needs. Who knows - this might lead to a whole new way of thinking about the clients' problems, leading to innovative solutions in analyzing and visualizing data to uncover valuable insights.
Consultants can see Agile - central to new data analytics tools implementation - as a foreign concept
Consulting teams traditionally operate in a "waterfall" fashion: they define an initial hypothesis, collect data to generate insights, and then present recommendations for clients. In technology, product teams rarely have the full picture upfront - they approach product discovery as well as delivery in an iterative fashion, correcting the course as they refine their understanding of the customer needs and technology constraints. Therefore, product teams need to align with their business counterparts not only on the product vision (the 'what'), but also the implementation approach (the 'how'), so that they truly embrace rapid learning and experimentation.
Successful digital transformation always requires an orchestrated effort to accelerate implementation of the new digital tools and processes. This requires the right structural and cultural elements, and the Agile mindset implies that the teams develop the ability to self-organize and quickly adapt to changes as they learn new information.
Modernization requires commitment - and sometimes you'll need a leap of faith
Efforts to modernize data analytics and visualization at consulting companies may be hindered by legitimate concerns over the return on investment and changes in the engagement models. For this reason, leadership teams at consulting companies often involve themselves in time-consuming discussions and evaluation rounds, looking to meticulously analyze risks and trade-offs when comparing legacy data solutions with the new technologies. In fact, executives can get into debates on technology and product design choices even when the differences have no material impact on the organization's goals. It's better to avoid such situations - but how exactly?
Leadership should recognize that modernization of data tools isn't a one-and-done exercise - for most consulting companies, it's a multi-phase process. In most successful transformations, technology teams regularly review their progress and delivery plans and ensure alignment with their key stakeholders from the company leadership. This way, lengthy preliminary discussions are not going to impede the process of digital transformation - all the really important questions will be answered as soon as they arise, and only then.
Finally, in contemplating digital upgrades, business leaders at consulting companies need to face the fact that traditional effort-intensive tooling (for example, Excel, PowerPoint) cannot match the advanced capabilities and performance of modern data technologies.
wWhile it is important to understand the technology demands in detail, the strategic decision to modernize the data infrastructure and tooling should be made at an enterprise level, enabling the participating teams to move at the necessary speed. It takes a leap of faith - but this results in more efficient, easy-to-use software and better insights.
The Power of Strong Partnerships and Change Management
"To build quality client-facing solutions and truly empower consultants to deliver data-driven insights, strong partnerships with product design and engineering functions are critical", says Kirill Osipenko, "Building a great data analytics tool is just the starting point. Product teams need to think about change management, including product evangelism, user education, technical support, etc. According to a well-known product manager's mantra, 'no product adoption means zero value'. Therefore, focusing on successful outcomes and empowering business users should be the top priority for any consulting company looking to modernize their delivery processes and tools."
The Future of Consulting Lies in Embracing Technology
In conclusion, consulting companies must recognize the importance of leveraging data technologies to stay ahead of the curve. The future of consulting lies in embracing AI and Big Data and investing in data-supported capabilities. By remaining vigilant to the challenges outlined above and embedding data engineering teams across the organization, consulting companies can remain at the forefront of their industry and deliver high-value client service.
