Sun Tzu said, "Know yourself and know your enemy, and you will never be defeated in a hundred battles." More than two thousand years later, this still holds true in the bidding arena—only the way of "knowing your enemy" should have been upgraded long ago.
The old-fashioned way of "knowing your enemy" relied on asking around: having someone inquire, listening at dinners, chatting privately. It is hard to tell true information from false, and there are compliance risks. The new way of "knowing your enemy" should be built on public data.
First, know yourself. Before bidding, lay out your own side's situation clearly: directional coverage, core team, recent project undertaking records, and external collaboration network. Many people lose because they do not understand the other side well enough; in fact, more people lose because they do not understand themselves well enough.
Then, know your enemy. The other unit's situation in the same field can be seen quite concretely using MuchSci talent profiles:
· List of experts in related fields—public profiles, one by one;
· Project undertaking status—approval numbers, years, funding, all verified hard data;
· Team composition and training relationships—whether their strength is concentrated or dispersed, and who the key members are.
Note the scope: all these data come from public profiles and verified project details. Intelligence gathering is for "knowing yourself and knowing your enemy," not for digging into people's backgrounds—all information is publicly available from the other unit itself.
The rhythm of scouting, four steps:
Define the bidding field → check the other unit's experts → look at projects and team → determine a differentiation strategy.
The first three steps are collection; the fourth is the winning move. Put both sides' situations together, and you can usually see three scenarios: head-on competition (both sides are strong), differentiated competition (we have unique points the other side lacks), or abandon or ally (the gap is too large).Which path to choose is a management judgment; but seeing which paths exist relies on data.