For your team · Strategy Arena
Strategy & Competitive Advantage
Compete in a dynamic market — positioning, pricing, and timing against rival teams.
Strategy Arena is a head-to-head competitive-strategy simulation. Every team runs the same company (five products, one built for each segment: Traditional, Low End, High End, Performance, Size), and every team sells to the same buyers. Each round is a fiscal year: teams set each product's price, promotion and sales budgets, production and R&D targets (performance, size, reliability), plus capacity, automation, finance and training. A deterministic engine runs the whole market at once: each segment buys inside its price range and on fit, share rises steeply with fit, buyers walk away from overpriced or off-target products, and demand a team can't supply goes to its rivals. Each round starts where the last one ended (specs, inventory, awareness, plant and the balance sheet carry over), so commitments compound: R&D lands a round later, capacity takes a round to build, and selling it back loses money. AI rival companies fill classes of fewer than four teams, an AI entrant attacks the most profitable segment mid-game, and the Executive tier adds a supplier cost shock. Each round a team saves a short strategy statement with its plan (target segments, a generic strategy and why). After the round, "said vs. did" on Results checks the statement against what the team actually did, and Board Review's three AI board members (a CEO peer, a CFO and an activist investor) read the statement, the results, the rivals' moves and the team's answer to last round's question, then ask one question for next round. None of this changes the score: it is feedback. The interface is Bloomberg-terminal-style: dense, fast, focused on numbers and standings.
The leaderboard, Scorecard, Final Report and gradebook use one number, the Strategy Score: the equal-weight average of the four pillars below, each built from every round played, not just the last. Every teammate shares the team's score, and it is each student's suggested grade; once any team in the class claims a role, it is 80% of the grade and role credit the other 20% (half changing the parts of the decision sheet the student's role owns each round, or submitting the round as Strategy Lead; half round reflections of 40+ words).
Share of each segment a team sells in, against a fair share (1 ÷ the companies competing), weighted by units sold. Owning segments beats a thin slice of all five; class size doesn't move it.
How well each product fits its own segment's buyers (performance, size, age, reliability) against the class's real, difficulty-adjusted ideals, weighted by units sold.
Where a team's prices sit in each segment's range, weighted by revenue. It only counts while the team keeps its share.
Profit across every round against a fair share of the market's revenue. New equity is charged 10% a year, so issuing shares can't lift it.
Bloomberg-terminal-style standings and a persistent ticker show every team's rank on the Strategy Score, stock price, revenue, net income and segment shares, round by round.
Segments buy inside their price ranges and on fit; share rises steeply with fit, buyers walk away from bad offers, and unmet demand goes to rivals. Focus beats the middle, and cost leadership and differentiation are both viable.
Each round starts where the last one ended. R&D lands next round, capacity takes a round to build and sells back at half its book value, and automation trades lower labor cost for slower, dearer R&D.
AI rival companies fill small classes, an AI entrant attacks the most profitable segment mid-game, and the Executive tier adds a supplier cost shock: rivalry, the threat of entry and supplier power from Porter's five forces.
Each round the team states its target segments, its generic strategy (Porter's four plus best-cost) and why. Once the round publishes, Results checks that statement against where the team's revenue and money went, how many segments it really competed in, its prices in each range and its commitments, each with the number behind it. Feedback, not score.
After each round publishes, three AI personas (CEO peer, CFO, activist investor) read the team's statement, said vs. did, results, rivals' moves and its answer to last round's question, and grill it on coherence. Each gives praise, concerns and one pointed question; the least confident member's question is the one the team answers next round. One review per team per round plus one re-run, three model calls each; it doesn't change the score.
Performance × size: every product in the class and each segment's ideal for the round once it publishes. Before the round, the Market page gives research ranges (exact ideals on the Undergraduate tier).
Runs the class's decisions with no randomness: same inputs always produce same outputs. Repeatable, explainable, defensible when a team asks "why did our decisions produce this result".
Four roles split the sheet: Strategy Lead (the strategy statement, the answer to the board, submitting the round), Product Lead (R&D targets), Pricing & Marketing Lead (prices, promotion and sales budgets, the forecast) and Operations & Finance Lead (production, plant, finance, training). Each part of the sheet names its owner and records who changed it; after each round every student writes a short reflection from their role on what the Competitor Report and the Board Review showed, and the professor reads them all on one page.
5 rounds in the five-week format · 8 rounds in the eight-week or 14-week semester format, one round a week. Same engine and segments; more rounds gives more time for the drift-and-reposition arc to play out.
Designed for ~15-30 students in teams of 4-6. All teams compete in the same market; a class of one to three teams gets AI rival companies, so every market has at least four competitors. Each team splits four light roles (one student can hold two on a small team).
MBA strategy courses, business policy capstones, executive education in competitive strategy. Especially strong for groups who want measurable, repeatable competitive outcomes.
Head-to-head competition on strategy fundamentals: every team's pricing, capacity and R&D decisions affect every other team's outcomes, and commitments carry from round to round. Deterministic engine (no randomness, no AI judge on the outcome). On top, for feedback only: a strategy statement every round, a said-vs-did check of it, and an AI Board Review that asks whether what the team did follows from what it said.
One of many pre-authored prompts from the sim’s Round 1 closelibrary. Grounded in the team’s actual decisions and used as a scheduled teaching moment.
Round 1 closeWhere did you plant your flag?
Each team: in one sentence, which two segments are you playing for by R5, and which decision in R1 proves it? Point to the R&D target or the price you set, not the memo.
Canvas, Blackboard, Brightspace, Moodle via LTI 1.3. Students launch from your LMS with single sign-on; one-click grade publish posts scores back with the rubric breakdown as the comment.
Per semester. No platform fee, no per-section charge, no seat minimums. Institutional invoicing available.