How an effective analytics organization better enables digital transformation
Every year, industries are inundated with trends, some holding the potential to turn the tide and drive the next wave of innovation. Digital transformation is one such trend that cuts across industries and is expected to reach USD 1,446.36 Million by 2028, with North America in the lead.
Digital transformation is an umbrella term that encompasses many trends and requires the expertise of various business functions. At its core, digital transformation is about innovating business operations with customer centricity and bringing efficiency into the ecosystem to operate as a unified entity. Although technology may seem like the apparent first step towards digitization, it is important to understand that technology is an enabler—while transformation is a strategic direction for an organization.
During the virtual Marketing Analytics Summit 2022, speakers and representatives from analytics and data science teams from Microsoft, Atlassian, Deloitte (Canada), Publicis Sapient, Shopify and Ancestry, among others, spoke about data culture within organizations, the untapped opportunity that analytics hold to drive and promote digital transformation and how an analytics organization should be a multidisciplinary setup.
Veterans of digital analytics talked about how the practice initially came about with the insurgence of the internet. What started as gathering insights to optimize digital spend has graduated to become the custodian of the customer journey. The value of data has been established over the years, with businesses transforming themselves into data-driven organizations. But what are the core tenets of a data-driven organization? How does one begin the journey? What are the questions to ask, and what answers should you be looking to find?
The core tenets of any data-driven organization are the trifecta that was popularized in the infosec world by Bruce Schneier: People, Process and Technology.
Analytics is typically viewed as a siloed organization that resides somewhere in the middle of business and product/engineering teams. Polarity in the job description for an analyst position across organizations is a testament to how nascent businesses are in fully deriving value from analytics teams. Some businesses have adopted data at their core and have evolved from descriptive to prescriptive analytics, forging themselves ahead of the curve by understanding customer behavior and responding to their needs in real-time. Many businesses are still establishing their boundaries and exploring what data can do for them. But most businesses by now have realized the importance of creating a function that goes beyond reporting numbers retroactively.
Let’s look at how the three tenets can guide the setup of an analytics function that enables digital transformation:
People: The core of the business—people who make up an organization and people who interact with the organization, the brand and their product and services.
- If you are just formalizing your analytics team or are looking to evolve the center of excellence, it is important to understand the data literacy within the organization and their appetite to make decisions based on data. Having a clear view of each team’s trust quotient towards the data will not only help in introducing innovative solutions and defining KPIs, but it will also help establish a high-quality data pipeline.
- The C-Suite and executives are typically defined as the end users of insights, but as you drill down into the sources of those insights and analyze the data pipeline that feeds into it, you will see the teams that contribute to the macro view. These teams will define the boundaries of data collection and create a funnel of metrics that will feed into the organization’s overarching goals.
- Knowing the appetite of end users towards transformation is an important step when defining the vision of a data-driven organization. This helps you define and segment your users and provide a programmatic and structured way to transform. For example, investing in targeted marketing and remarketing towards a customer base that is wary of privacy would not result in the desired ROI and may also adversely affect the customer base.
- Digital transformation is fueled by customer-centricity, and it is important to include customers, external as well as internal, in decision making.
Process: With people being defined, the next steps would be defining the protocol of data collection, data storage and accessibility, deriving insights and executing recommendations and enhancements.
- Collaboration, or lack thereof, within teams is one of the biggest challenges that sometimes make analytics either reactive or duplicative. A scenario by speakers from Amplitude provided insight into how their product and marketing teams’ differing visions for a user journey amounted to competing objectives and KPIs. While the product team’s objective was to retain users and create a product that makes their life better, the marketing team was focused on getting users to the site and was unaware of what happens after a user visits. Although competing KPIs can be successful in the short term, with individual teams fulfilling their objectives, it is not strategic nor sustainable. Establishing protocols to create synergies between teams will create a holistic view of activities and create streamlined KPIs. This could include the introduction of a peer review process, an opportunity for your consumer (who may also be your employee or colleague) to understand the context of what teams are working on and why they are developing it. Getting buy-in for the service or solution at the beginning will not only get teams excited and help improve the product, but also contribute towards better data quality.
- For an organization to be data-driven, it is important to enable everybody in an organization, regardless of their technical knowledge, to work with data comfortably and to feel confident in making data-informed decisions. The responsibility of the analytics team is not just to distill complex data into insights, but for it to be easily accessible and digestible by users as well. Data democratization is not just empowering; it also removes bottlenecks from the analytics team. To successfully democratize data, it is important to establish clear data governance, security and ownership protocols to ensure user data is not vulnerable to data breaches.
- Establishing processes is an ever-evolving exercise and requires regular audits between multiple groups and the overall business. It requires you to keep a pulse on changing consumer demands and be nimble and creative in modifying processes to cater to the changes you uncover.
Technology: This is probably one of the most discussed aspects when talking about digital transformation. Although it is important to broaden your technology capability to sustain and scale operations and introduce automation, it is important to remember that technology is an enabler and not a proponent of transformation.
- Before choosing a technology from the latest trends report, conduct an audit of the current ecosystem and available tools. This audit should also include current literacy of these tools within the organization. While licensing cost is apparent, assess the training cost of the tool, both for users who interact with it frequently and viewers, such as the C-suite, who use it as quick reference material.
- Tier the users based on frequency of use. This will also help define usability and design. For example, if multiple databases are joined to create dashboards in Power BI to be used by the sales force daily, what is the latency of queries? If your team uses it on the go, is the design mobile friendly?
- Establishing process and protocol breeds an environment of collaboration and eliminates multi-analytics product issues. As businesses and business leaders evolve, they choose products that are familiar. This decision is also very team specific and does not consider existing tools used by other teams and potential expertise that lies across teams.
- This bifurcates an otherwise holistic view of a user journey (e.g., if product and marketing teams were to use two different tools to map the user journey, the view of one John Doe now exists in two different ecosystems). While insights from two or more sources can be joined in an external data warehouse to create a full journey, it is likely a cost-intensive exercise. It may also adversely affect the data quality.
Synergies between people, process and technology will enable businesses to create a connected strategy (as proposed by authors Nicolaj Siggelkow and Christian Terwiesch) that enables organizations to respond to users’ desires, curate their offerings, coach their behavior and automate the delivery and execution. When talking about how a connected strategy can create a unified experience, Mehwash Zafar, Senior Specialist—Performance Marketing at Deloitte Canada, discussed the introduction of MagicBand by Disney. This provided Disney the ability to capture the customer journey and create a personalized, seamless and magical experience for the customer. It has also improved Disney’s productivity and resource allocation to meet user needs.
Transformation begins with customers—both understanding them better and interacting with them efficiently. The biggest hindrance in transformation efforts is operating in silos. At the onset or during the evolution, utilize and consolidate the data collected across multiple touch points and identify the crossover to hone in on the opportunity areas. Initial distilling of information across multiple touchpoints will provide dots on a map, and, with the right communication and collaboration across the business, those dots can be connected to point towards the north star!
Photo Credit: Conny Schneider | Unsplash