Building a Successful Analytical Organization

Making better decisions and taking the right actions requires organizations to use analytics. Advances in technology are creating a data-driven revolution. Companies with the right analytics infrastructure and the right talent in the right places have a significant competitive advantage. A 2019 Deloitte study of 1048 executives revealed that 80% of organizations identified as having a mature approach to data analytics exceeded their goals, and 48% significantly-exceeded their goals. To maximize an organization's analytical potential, talent needs to be structured in alignment with the organization's culture and mission. It is projected that the demand for technological, social, emotional, and higher-level cognitive skills will continue to increase as we approach 2030. To avoid costly mistakes and increase revenue, organizations need to identify the right analytical skills and assess their organizational design.
The Right Analytical Skills
Analytical skills include more than the obvious need for technical competence with coding and applications for modeling, forecasting, and statistical analysis such as SPSS, R, and Python. For organizations to be effective with data analytics, they need employees with business process knowledge and skills in:
negotiating
consulting
communication
developing others
quantitative analysis
Organizations also need analytical leadership at every level, not just in the C-suite. Beyond being good leaders, analytical leaders:
possess a passion for data analytics
make data-driven decisions
commit to results
develop others analytical capabilities
set strategy with analytic performance metrics
seek out and exploit quick wins for analytics
take a long-term view of analytics
grow their analytical networks
utilize project portfolios to work across the business and within the limitations of data analytics
Leaders and employees with analytical knowledge, skills, and abilities are shaping the future of the workplace. There is a high demand for these employees, and it is very challenging to source, recruit, and retain those who possess these analytical attributes. Having the right talent strategy and being clear on the analytical skills your organization needs will help companies compete for the talent to build a successful analytical organization.

Building and Assessing Your Analytical Organization

Having the right talent with the right skills is not the only challenge. An organization's culture is the one thing that impacts everything. Creating and managing culture are essential activities for leaders. Having an analytical orientation within the organization's culture is vital to building a successful analytical organization. An organization's perceived value associated with analytics directly influences decisions on the best way to align analytical resources across the business.
A critical mass of analytical talent is essential to making better data-driven decisions and determining the optimal organizational design. The following is a simple organizational assessment a leader can use to enhance their talent management, development, and recruiting strategies (see Table 1). The evaluation involves counting the number of human analytical resources across the organization and assessing their depth of analytical capability within three categories of analytical tasks:
Level 1: capable of workbench, standard reports, and alerts
Level 2: capable of multidimensional analysis, analytical applications, and data visualization
Level 3: capable of what-if planning, predictive modeling, and statistical analysis
Once you can visualize the organization's analytical talent structure and capability, it is easier to identify talent strengths and opportunities.

Note: This table is an example used to demonstrate a hypothetical organizational analytical skills assessment adapted from Davenport et al. (2010).
The organizational design challenge is placing the analytical resources close enough to the business to focus on the most critical initiatives while still enabling mutual learning across the analytical resources. This design decision needs to take into consideration the organizations' analytical culture orientation and maturity.
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References:
Bartlett, R. (2013). A practitioner's guide to data analytics: Using data analysis to improve your organization's decision-making and strategy. McGraw-Hill. New York.
Bughin, J., Hazan, E., Lund, S., Daholstrom, P., Wiesinger, A., & Subramaniam, A. (2018, May 23). Skill shift: Automation and the future of the workforce. McKinsey Global Institute. https://www.mckinsey.com/featured-insights/future-of-work/skill-shift-automation-and-the-future-of-the-workforce
Davenport, T. H., Harris, J. G., & Morison, R. (2010). Analytics at work: Smarter decisions, better results. Harvard Business Press. MA.
Deloitte. (2019). Deloitte survey: Analytics and data-driven culture help companies outperform business goals in the age of with’. https://www2.deloitte.com/us/en/pages/about-deloitte/articles/press-releases/deloitte-survey-analytics-and-ai-driven-enterprises-thrive.html
Grossman, R. L., & Siegel, K. P. (2014). Organizational models for big data and analytics. Journal of Organization Design (Aarhus), 3(1), 20-25.
Indeed.com. (2020, November 23). Analytical skills: definitions and examples. Indeed Career Guide. https://www.indeed.com/career-advice/resumes-cover-letters/analytical-skills
Schein, E. H. (2004). Organizational culture and leadership (3rd ed.). Jossey-Bass.
Tambe, P. (2014). Big data investment, skills, and firm value. Management Science, 60(6), 1452-1469.

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