Agility and the Analytic Sandbox


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:

  1. Scenario Planning (for options, pessimistic/optimistic, best case/worst case, etc …)
  2. Capital Planning
  3. What-If planning, Pricing
  4. Activity-Based Budgeting
  5. Data Exploration / insights (i.e. Tell me something I don’t know)
  6. Simulation
  7. Risk Management
  8. Strategy and Planning Dashboard  (linking strategy with objectives, goals and metrics)
  9. Forecasting / Predictive analytics
  10. Marketing Management / Social Media Analytics
  11. Supplier, Facility, IT, Human Resource and Capacity Planning
  12. Product Planning

Elements of detailed business planning and budgeting:

  1. S&OP / Supply and Demand Planning
  2. Optimization (inventory, production, logistics, marketing, etc …)
  3. Disaggregated forecasts
  4. Operational plans (PLM, production control, procurement, logistics, after-market service, maintenance, etc …)
  5. Departmental, Project and Program Budgets / Resource Allocation

Elements of Execution Management:

  1. Operational Dashboards
  2. Control Tower
  3. Quality Control
  4. Measurement, Metrics / Closed-loop and OODA Feedback (to strategy and business planning)
  5. Event Stream Processing / Decision Management
  6. 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!


About Author

Leo Sadovy

Marketing Director

Leo Sadovy currently manages the Analytics Thought Leadership Program at SAS, enabling SAS’ thought leaders in being a catalyst for conversation and in sharing a vision and opinions that matter via excellence in storytelling that address our clients’ business issues. Previously at SAS Leo handled marketing for Analytic Business Solutions such as performance management, manufacturing and supply chain. Before joining SAS, he spent seven years as Vice-President of Finance for a North American division of Fujitsu, managing a team focused on commercial operations, alliance partnerships, and strategic planning. Prior to Fujitsu, Leo was with Digital Equipment Corporation for eight years in financial management and sales. 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 a Masters in Analytics, an MBA in Finance, a Bachelor’s in Marketing, and is a SAS Certified Data Scientist and Certified AI and Machine Learning Professional. He and his wife Ellen live in North Carolina with their engineering graduate children, and among his unique life experiences he can count a singing performance at Carnegie Hall.


  1. Patrick van Loon on

    I couldn't agree more that, as they stand today, Control Towers are focused on the operational/tactical execution of for example Supply Chains. However, the question is if that is by design or just a reflection of current practice. Having worked in the Logistics Industry for the last 15 years, and being directly involved in one of the worlds first global Control Towers, I'm of the opinion this is something that just today's practice, and will need to change soon.

    The concept of 4th party logistics (4PL) was introduced about 12 years ago by Accenture. These 4PL's would focus on the strategic structure of the supply chain network, and source multiple 3PL's (Logistics Service Providers) to perform the necessary warehousing and transportation services. The idea behind the 4PL was to introduce more strategic thinking, more sophisticated processes and more advanced techniques to bring the supply chain to a next level. Vector SCM, a joint venture between General Motors and Conway, was such a 4PL and incorporated in 2004. Vector dramatically changed the way GM was looking at their supply chain(s) and brought about fundamental shifts in its logistics foundation. GM realized through the success of Vector that Supply Chain Management was a strategic asset for them, which led them to buy-out Conway in this 4PL concept and run the Control Tower themselves.

    Over the years many other forms of 4PL's have emerged, and the most common naming for them has become Control Towers. Another term heard often is Lead Logistics Provider. But what most of them lacking is, as mentioned in your blog, a strategic focus. Many of them are just another management layer on top of the warehousing and transportation service providers already in place. As such, they replace the Logistics Department of their customers without bringing too much added value or innovation. This in itself is not a sustainable model - without constant innovation the savings that can be achieved will diminish over the years and the customers will no longer be willing to pay the premiums required for a Control Tower. By design the Control Tower can only exist if it brings innovation. And too bring innovation, they need to do things in a different way then before. That's where Business Analytics come in.

    Control Tower are sitting on enormous amounts of (supply chain) data, and are generating and collecting more data everyday. How is this data used today ? Not at all, maybe only to investigate what went wrong once the issue already has surfaced itself. Applying Analytics to this wealth of Data can bring about the innovation required to survive as a Control Tower. Not only to pro-actively adapt the supply chain but also by turning the data into valuable information for other parties, thus creating a new service and revenue stream for the Control Tower. Who knows better about the buying behavior of households then the company that manages the deliveries of multiple stores to their address ?

    In my opinion it is not a question of Control Towers versus Analytics; they go hand in hand. Control Towers are here to stay as they bring focused attention to the business process they control. But only if they embrace Analytics will they be able to prove their value and survive.

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