Business entropy is almost inevitable as an organization grows. This property contributes towards enterprise complexities now more than ever due to evolving business models, rising consumer expectations, and skyrocketing technology innovations. It breeds uncertainties in business strategies and decision-making. Despite the perennial need to manage such uncertainties in businesses, there are no comprehensive frameworks that incorporate such uncertainties, their antecedents and help in establishing a clear linkage from strategies to expectations and outcomes.
Business uncertainties require constant leadership intervention to turn the wheels forward towards decisions that are laced with a sense of urgency, relevancy, accuracy and impact. However, this decision-making process is not without its challenges.
The surge of new technologies and the visibility of data has instilled a new hope to ease the entire decision-making process. Functional leaders are leaning towards harnessing the power of data coupled with business knowledge to understand scenarios and related implications to make informed decisions. While it is an advancement from a heuristic and intuition-based decision-making process, many times functional owners formulate decisions that are focused more on their respective functional outcomes than being aligned to an overall business goal and an outcome. In a way, they operate in a “Siloed data-driven decision-making world”.
Inside a Siloed World
Striking the right balance between business decisions and organizational goals is a herculean task. Traditionally, organizations have mostly been focused on leveraging historical data and past results in silos to answer business problems. Just trying to unravel the mysteries around “How was the sales of a product in the western US region over the last few quarters?” in isolation, would not provide an accurate indication of the business performance. It misses out vital connections to other key drivers which are influencing sales performance such as marketing efforts, outreach for prospects, promotions, competitive market space or pricing, product adoption, customer success influence, features or differentiation, support & service experience and customer satisfaction. Hence, such a siloed lens does not help in understanding which strategy is working versus which one is contributing to the success.
Missing top-down synchronization: The hierarchy of objectives necessitates that all cross-functional teams in an organization align seamlessly to achieve corporate goals. However, due to the serious lack of shared vision and culture of a company, functional-level KPIs do not often roll up to enterprise-level strategic checkboxes. For Instance, if a corporate goal is to increase the subscription revenue, it is not just the responsibility of the Sales function to sell subscription products, but also a collaborative effort by cross-functional teams to improve campaign conversion, renew existing customers and encourage cross-sell and upsell. The journey starts with the Customer Success team addressing a customer’s pain points for better adoption and churn prevention, the Product team addressing feature gaps to meet customer needs and help retain or attract new customers, the Support team to enhance customer support experience through faster case handling and the Marketing team to attract new leads, cross-sell and upsell.
Disconnected Metrics: When setting up success criteria for key metrics, enterprises often miss the bull’s eye. It could be that the marketing function is stirring up positive curiosity about a product and is viewing lead-generation forms being filled up as a success parameter, while the reality highlights supply chain breakage due to unforeseen weather conditions. This metric lineage breakdown causes a ripple impact in not meeting a company’s overall objective.
Metric accountability: The ability to connect the deep domain expertise from functions to drive corporate objectives rests on the clear definition and the ownership of functional metrics that collectively contribute towards corporate metrics. For instance, if Monthly Recurring Revenue (MRR) as a metric is owned by the Renewal team, the team stakeholders are dependent on the upstream functions to accurately capture Sales data attributes, Booking data, Onboarding users data, Provisioning or fulfilment data, Usage and Billing information, thus, enabling the Renewal team to derive the MRR consistently and in a timely manner. Such connectedness is required to avoid overall obstruction of organizational growth and scaling.
Hence, “Connected insights-driven decision-making process” provides a better influence in defining the right strategies by connecting data and interventions to propel a business forward for growth and changing existing market dynamics to work in favor.
In A Connected Universe
The concept of connected Intelligence has been around for decades. Today’s technological evolution supports this concept and is a culmination of several trends that has manifested over time. From the early days of telemetry to machine-machine connectivity to the Internet of Things, these tech-trends have played critical roles in this evolution journey.
With 463 exabytes of data estimated to be created each day globally by 2025, the potential for enterprises to inject actionable insights at the point of decision formation is immense. In this connected business world, we must change gears by delivering both operational data and “Connected data-driven Insights” at the edge of consumption with speed and accuracy as part of a process flow or customer journey. This can be effectively done by enabling key data across all key functional domains, in conjunction with the data derived from external market events such as competition data, customer business health, Intent, social data and local government policies towards targeted industries.
The sooner the importance of democratization of data-driven decision-making is realized, the easier it would be for enterprises to drive desired impact.
Make data-driven culture an omnipresent reality: The fundamental building block to achieving connected data-driven insights in any enterprise is its ability to create a collaborative data-driven mindset. It is a habit that trickles top-down. It is important to encourage a culture of continuous learning, knowledge-sharing and open communication among stakeholders, customers, partners and employees. Departments should establish leading and lagging business performance indicators(KPIs) to identify gap drivers. This, in turn, will help in choosing success metrics with care, confidence and help in forming well-rounded decisions to enable corporate direction.
Contextualize data as part of the operational process to drive decisions: Having contextual access to trusted data and understanding how one might interpret it to drive business decisions, will help in streamlining operational processes and ultimately delivering superior customer experience. Contextualization of data can be achieved effectively through augmenting insights as part of business processes. Embedding advanced analytical models into process workflows will help empower leaders to fine-tune decisions and automate processes in the context of outcomes and behaviors.
Maximize data consumerization by expanding consumption choices: With the power of analytics and capabilities around analyzing data real-time, it is essential to weigh in the option to embed insights as part of the system of engagements (Transactional applications). It is important for an analytics-driven team to rethink fundamental approaches, compare alternatives and provide choices to drive enterprise-wide consumption of data and insights.
Shaping an organization, which can withstand and anticipate the entropy of a future market is exciting and challenging. Implementing a robust roadmap to acquire and consume trusted data as well as spearheading initiatives to build infrastructures for supporting the effective distribution of insights, are the necessary steps that guarantee connectedness and collaboration to achieve actionable decisions and successful business outcomes.
By Arvinder Singh (CEO, Enquero – A Genpact Company) and Venkatachalam Ramasubban (SVP- Data Analytics, Enquero – A Genpact Company)