“Whether you’re found­ing a start­up, report­ing results, or shap­ing an invest­ment strat­e­gy – every­thing comes back to impact. Impact mea­sure­ment is a key tool for any orga­ni­za­tion that wants to under­stand its con­tri­bu­tion to sus­tain­able devel­op­ment and the UN Sus­tain­able Devel­op­ment Goals. So the real ques­tion is: how can we design and apply impact mea­sure­ment meth­ods that actu­al­ly work?”

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Felizia von Schweinitz, PhD Can­di­date and Project Lead, Impact Mea­sure­ment and Val­u­a­tion Lab (IMV-Lab), Uni­ver­si­ty of Ham­burg

I don’t want to miss a thing … Holis­tic impact mea­sure­ment

Whether you’re found­ing a start­up, report­ing to stake­hold­ers, or shap­ing an invest­ment strat­e­gy – every­thing revolves around impact! Impact mea­sure­ment is a core tool for any orga­ni­za­tion that wants to under­stand how it con­tributes to sus­tain­able devel­op­ment and the UN Sus­tain­able Devel­op­ment Goals. Done right, it helps build legit­i­ma­cy with stake­hold­ers and can even improve access to fund­ing.

Holis­tic impact mea­sure­ment: Inputs — Out­puts — Out­comes — Impact

Log­ic mod­els (like the IOOI mod­el) make it eas­i­er to under­stand and mea­sure orga­ni­za­tion­al impact. They map how inputs (e.g., fund­ing) lead to out­puts (e.g., work­shops), which then gen­er­ate out­comes (e.g., improved skills or well-being for par­tic­i­pants) – and ulti­mate­ly con­tribute to long-term soci­etal impact (e.g., high­er qual­i­ty of life).

But here’s the chal­lenge: many impact mea­sure­ment meth­ods on the mar­ket aren’t open source or sci­en­tif­i­cal­ly reviewed. They’re pure­ly prac­tice-dri­ven. That becomes a prob­lem when these meth­ods claim to reflect holis­tic impact – but actu­al­ly don’t. A com­mon exam­ple is mon­e­tary val­u­a­tion meth­ods. These often count only the quan­tifi­able out­puts (like the num­ber of train­ings offered) and mul­ti­ply them by a mon­e­tary fac­tor. They try to esti­mate “impact” based sole­ly on out­puts, with­out mea­sur­ing real out­comes in the tar­get group. And that’s a big issue. The num­ber of work­shops deliv­ered (out­put) tells you noth­ing about the qual­i­ty of those work­shops or the long-term effects on par­tic­i­pants (out­come). Yet many still label this “impact.”

So how can we design and use impact mea­sure­ment meth­ods that actu­al­ly work?

1. Use sci­en­tif­ic meth­ods, peer review, and full trans­paren­cy

Holis­tic impact mea­sure­ment has to go beyond count­ing out­puts. To under­stand real soci­etal impact, you need to mea­sure out­comes with­in your tar­get group, not just activ­i­ties. Research helps by pro­vid­ing sol­id clas­si­fi­ca­tion meth­ods, trans­par­ent devel­op­ment process­es, and a crit­i­cal under­stand­ing of where impact mea­sur­ment works well and where it has lim­its.

2.Build meth­ods co-cre­ative­ly – bridg­ing prac­tice and sci­ence

To cre­ate tools that are both rig­or­ous and prac­ti­cal, devel­op­ment should be co-cre­ative: prac­ti­tion­ers and experts work­ing togeth­er through work­shops and feed­back loops. The The IMV-Lab’s Impact Mea­sure­ment Hand­book was cre­at­ed this way, as part of a BMBF research project by the Uni­ver­si­ty of Ham­burg and LMU Munich along­side impact-com­mu­ni­ty part­ners. What’s new? The hand­book helps orga­ni­za­tions apply sci­en­tif­ic approach­es while look­ing at all lev­els of impact: inputs, out­puts, out­comes, and long-term soci­etal impact. It also tack­les a key ques­tion head-on: when does it make sense to mon­e­tize out­comes – and when is it actu­al­ly valid to do so?

3.Reporting com­plex impact – sim­pli­fy, but not too much

Impact data needs thought­ful use and care­ful aggre­ga­tion. Over­sim­pli­fy­ing can erase impor­tant nuances and even fuel accu­sa­tions of green­wash­ing. Because sus­tain­abil­i­ty chal­lenges are com­plex, our mea­sure­ment approach­es must reflect that com­plex­i­ty. Only then can lead­ers make impact-informed deci­sions. A strong approach is to com­bine quan­ti­ta­tive and qual­i­ta­tive eval­u­a­tion meth­ods. Togeth­er, they paint a clear­er and more accu­rate pic­ture of social and envi­ron­men­tal impact.

Beyond pure mea­sure­ment, the IMM­PACT mod­el gives orga­ni­za­tions a roadmap for how to evolve their impact sys­tems – step by step – from sim­ple out­put track­ing toward sys­tems that are:

- more com­pre­hen­sive

- focused on out­comes and long-term impact, and

-  ful­ly inte­grat­ed into orga­ni­za­tion­al strat­e­gy.

Feli­cia von Schweinitz (PhD Can­di­date and Project Lead, Impact Mea­sure­ment and Val­u­a­tion Lab (IMV-Lab), Uni­ver­si­ty of Ham­burg)

Felizia von Schweinitz is a PhD can­di­date at the Chair of Sus­tain­able Busi­ness (Prof. Dr. Lau­ra Marie Edinger-Schons) at the Uni­ver­si­ty of Ham­burg. She leads thet Impact Mea­sure­ment and Val­u­a­tion-Lab (IMV-Lab), a project fund­ed by the Ger­man Fed­er­al Min­istry of Edu­ca­tion and Research and car­ried out in part­ner­ship with LMU Munich. As part of Germany’s Nation­al Strat­e­gy for Social Inno­va­tions and Social Enter­pris­es, the IMV-Lab aims to strength­en impact trans­paren­cy in social inno­va­tion. Its mis­sion is to sys­tem­at­i­cal­ly advance the field of impact mea­sure­ment for social inno­va­tions and pro­vide resources that help orga­ni­za­tions bet­ter com­mu­ni­cate their impact.