How do we best ingrain analytics into the organization’s decision-making processes?

How do we best ingrain analytics into the organization’s decision-making processes?

Adopting the analytics philosophy in the communications department and the whole business, decision-making processes will necessitate the statement of the department’ and the business strategic goals first. The department and the entire organization’s strategic objectives must agree that the inculcation of analytics will improve, in part the business processes, and consequently lead to the attainment of the objectives set (Knobbout and Van der Stappen, 2020). The decision-making policies must be in line with the fact that the department and the business require transformation, to not only achieve internal objectives but also gain a competitive advantage. Essentially, the establishment of analytics depends entirely on the policies that guide decision-making, being in line with required technological advancements.

To establish analytics in the decision-making process of the communications department and the business, they both must first define the most relevant data and analysis strategies and tools. In the communications department, the data and analysis methods should facilitate the achievement of the organization’s strategic objectives. As such, these methods and tools should be in line with the policies of the company, allowing the use of statistical and data mining methods in creating new solutions. The tools must be able to perform visualizations that are model based, on putting actions in the hands of the systems. When such measures are put in place, inculcating analytics becomes easier.

Additionally, to best ingrain analytics, it is salient that decisions are re-engineered to use outputs including insights and analysis obtained from the analytics. The current decision-making processes and policies are not in line with the recommended strategic objectives. Therefore, the decision-making policies must be reshaped, and designed such that the department and the business’s operations can run unaltered, and particularly achieve improvements in the intended areas.

How do we organize and coordinate analytics capabilities across the organization?

To effectively coordinate and organize analytics capabilities across the communications department and the entire organization; it would be statistically reasonable to adopt a cross-functional approach to activities, processes, roles, and responsibilities. The approach requires designing an appropriate departmental and company construct that allocates resources based on the level of need in a specified section. It involves the examination of the department and the entire business and identifying and assessing areas where analytics will facilitate significant value and that aligns with the decision-making policies. Indeed, it requires the evaluation of the demand and the effect of supply in areas that need the installation of Analytics.

However, the coordination of analytics has no one right strategy, and the communications department may require a different model of organizing analytics capabilities from that of the business. Despite this fact, several factors form the grounds for the formation of a suitable model that can allow organization and coordination for any area as deemed fit (Knobbout and Van der Stappen, 2020). They include outcome measurement processes, use of insight-driven decisions, information and data management tools, department and organization structure and talent management, governance and sponsorship, and capability development strategies.

The communication department and the company should lobby for executive support in leadership and decision-making. The leaders must align their leadership to the vision that analytics embodies. Both should assess their structural ability, including talent availability, and available skills, that can facilitate the establishment, and organization of the analytics transformation process. Both must have the ability to process insights, and effectively incorporate them into their decision-making procedures, to facilitate the creation of smarter decisions.

How should we source, train and deploy analytics talent?

Sourcing analytics talent begins with the understanding that such talent is scarce. Scarce because, with the ongoing transformations in the use of big data, data scientists, for example, are in high demand in every industry. However, with the realization of the growing need for experts in analytics, universities and institutions are offering programs in data science, with specializations in specific areas such as communication, health, or finance. Talent can be sourced internally, or externally. Internally, talent can have sourced by upskilling certain employees. Externally, talent can be sourced from public or private partnerships, or hired from offshore or onshore for specific periods.