Analytics gives us not just the ability but the imperative to separate our planning activities into two distinct segments – detailed planning that leads to budgets in support of execution, and high-level, analytic-enabled business/scenario planning.
My critique of Control Towers in this blog last time led me not only to consider the role and relationship a control tower might play in the planning process, but also to evaluate the overall planning process itself. This appraisal has in turn caused me to reassess the approach I introduced some time ago in this post, “Rolling forecasts, or Who ordered that?” and to restructure the diagram representing my view of the ideal business planning process.
In that previous structure I envisioned a three-level process structure, with the Strategic Plan and the Forecast at the highest level, informing an 18-month rolling PLAN (not forecast) in the middle tier, driving the Budget(s) at the lowest level.
In my last post I somewhat castigated the emerging universal control tower approach, which purports to solve practically all your business problems including hunger and world peace, an approach where the overstuffed control tower included capabilities spanning from analytics to simulation to alerts to dashboards. I tried to make the case that the control tower is fundamentally tactical and best suited to supporting operational execution – it’s not a strategic platform.
But still, there does seem to be the need for a control-tower-like capability in support of strategy and high level planning, an agile capability that mirrors at the strategic level the executional agility a control tower provides at the operational level – an entity which I am going to label the Analytic Sandbox. Not a new concept to be sure, but refining the definition of its proper role does help to clarify its relationship to the overall business planning process.
The key insight is to keep this analytic package together, but to deploy it where it does the most good, not in support of execution, but in support of scenario planning. This in turn requires dividing our current monolithic planning process in two – the detailed single-scenario plan that eventually spawns an equally detailed budget, and the high-level business planning where agility has recently become paramount if not mandatory. Resident inside of this business planning process is the Analytics Sandbox – a combination of agility with the power to know.
Elements of high-level Business Planning with the Analytic Sandbox:
- Scenario Planning (for options, pessimistic/optimistic, best case/worst case, etc …)
- Capital Planning
- What-If planning, Pricing
- Activity-Based Budgeting
- Data Exploration / insights (i.e. Tell me something I don’t know)
- Simulation
- Risk Management
- Strategy and Planning Dashboard (linking strategy with objectives, goals and metrics)
- Forecasting / Predictive analytics
- Marketing Management / Social Media Analytics
- Supplier, Facility, IT, Human Resource and Capacity Planning
- Product Planning
- …
Elements of detailed business planning and budgeting:
- S&OP / Supply and Demand Planning
- Optimization (inventory, production, logistics, marketing, etc …)
- Disaggregated forecasts
- Operational plans (PLM, production control, procurement, logistics, after-market service, maintenance, etc …)
- Departmental, Project and Program Budgets / Resource Allocation
- …
Elements of Execution Management:
- Operational Dashboards
- Control Tower
- Quality Control
- Measurement, Metrics / Closed-loop and OODA Feedback (to strategy and business planning)
- Event Stream Processing / Decision Management
- Digital Marketing
- …
While both concepts enable organizational agility, what I think the difference is between a Control Tower and an Analytics Sandbox is the scale of the response. The Control Tower is about the agility to adjust near-term operations in order to meet customer expectations and obligations; the Analytic Sandbox is about the agility to adjust organizational strategy and associated business plans in the face of market forces.
We are accustomed to being agile with our operational execution – no organization gets through the day without making dozens if not thousands of little adjustments along the way. Whether or not we have a formal Control Tower, we have been doing control-tower-like activities forever. What has not yet become commonplace are the tools and approaches that allow us to extend that agility to the larger scale and scope of the entire organization and its strategic concerns. Not commonplace yet, no, but available, YES – Analytics and the Analytic Sandbox, most definitely, YES!
By Leo Sadovy, from:
Leo Sadovy handles marketing for Performance Management at SAS, which includes the areas of budgeting, planning and forecasting, activity-based management, strategy management, and workforce analytics, and advocates for SAS’ best-in-class analytics capability into the office of finance across all industry sectors. Before joining SAS, he spent seven years as Vice-President of Finance for Business Operations for a North American division of Fujitsu, managing a team focused on commercial operations, customer and alliance partnerships, strategic planning, process management, and continuous improvement. During his 13-year tenure at Fujitsu, Leo developed and implemented the ROI model and processes used in all internal investment decisions—and also held senior management positions in finance and marketing.Prior to Fujitsu, Sadovy was with Digital Equipment Corporation for eight years in sales and financial management. He started his management career in laser optics fabrication for Spectra-Physics and later moved into a finance position at the General Dynamics F-16 fighter plant in Fort Worth, Texas.He has an MBA in Finance and a Bachelor’s degree in Marketing. He and his wife Ellen live in North Carolina with their three college-age children, and among his unique life experiences he can count a run for U.S. Congress and two singing performances at Carnegie Hall. See Leo’s articles on EPM Channel here.