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How to price Enterprise Social Computing offerings?

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Inno­va­tion is obvi­ous in the Enter­prise Social Com­put­ing field. Fea­tures are invented and com­bined in novel ways; ever chang­ing suites of prod­ucts are built and mar­keted. Inno­va­tion is very real, even if not of the scale sig­naled by the hype around it. It’s not in pric­ing how­ever. Even worse: pric­ing is often struc­tured con­trary to the value offered and hin­ders both pilot and full deployments.

Look at the met­rics, fences, and whole pric­ing strate­gies of your favorite ven­dors. Strat­egy may even be too strong of a word, as they often are a com­bi­na­tion of clas­sic scale met­rics (per user per month), setup and deploy­ment fees that are pure cost pric­ing, bland and rigid Volume-Discount price structure.

Ven­dors should exploit the prin­ci­ples of value pric­ing on a much wider and deeper scale than they cur­rently attempt to. Value pric­ing is obvi­ously noth­ing new, yet it seems strangely ignored by both ven­dors and their clients. Prac­ticed in the emerg­ing IT field, it will have deep impacts for both ven­dors and clients and will spur a much more pro­duc­tive col­lab­o­ra­tion between the two.

Value and cost are not matching

Every prod­uct bear­ing what is usu­ally dubbed a “social com­po­nent” has sig­nif­i­cant net­work effect and peer pro­duc­tion dynam­ics. The more employ­ees actively use the appli­ca­tion, the more they — and so their orga­ni­za­tion — extract value out of its use. Mar­ginal ben­e­fit per user, and hence total value, thus increases with the num­ber of active users. Yet, most pric­ing struc­ture are degres­sive, Volume-Discount schemes: price per user decreases with the num­ber of users. Price and value varies in oppo­site ways:

slide7.007.png

What hap­pens here is a total rever­sal of what should be aligned: the more employ­ees use the sys­tem, the more value you get out of it per user, the less you pay. And the less users you have, the less value you get, the more you pay. This explains both the refusal of lots of com­pa­nies to pilot new tech­nolo­gies, and the dif­fi­culty to tran­si­tion from pilots to full deploy­ment: if you can’t do it in one shot, the eco­nom­ics will be much less in your favor to do it in a phased way.

Align­ing value and cost decreases risks for large clients

When com­pa­nies are look­ing to pilot inno­v­a­tive tech­nolo­gies, they con­sider both the pilot itself and the full deploy­ment — of which the pilot is just the first step — if it ever hap­pens. But they also eval­u­ate half-successes: what hap­pens if they need to deploy only across half their planned user base? Com­pa­nies will do a pilot, agree­ing before­hand to a price struc­ture that sees the price decrease as the num­ber of users increases. ROI cal­cu­la­tions will more often than not be based on opti­mistic expec­ta­tions towards the adop­tion rate, over­es­ti­mat­ing the price dis­count. So what hap­pens if you planned on deploy­ing the piloted tech­nol­ogy across 10,000 users and find out you have to start with 1,000 and demon­strate the value over time? Well, your price per user will likely shot up significantly.

This means that, with clas­sic Volume-Discount pric­ing struc­tures, com­pa­nies will usu­ally have the choice between a full deploy­ment or no deploy­ment. Deploy­ing on a smaller scale would decrease the ROI sig­nif­i­cantly as it low­ers the value and increases the costs. Unfor­tu­nately, what this means is that dis­rup­tive inno­va­tions, where the value is by def­i­n­i­tion not obvi­ous for stake­hold­ers, and where it usu­ally emerges from early adopters expe­ri­ence, are very dif­fi­cult to suc­cess­fully tran­si­tion from pilots to pro­duc­tion. They would need a phased deploy­ment, start­ing small and scal­ing up pro­gres­sively, that is not prof­itable with a Volume-Discount price scale.

By pric­ing their soft­ware closer to the actual value deliv­ered and per­ceived by their clients, ven­dors will get pilot deploy­ments accepted much more eas­ily, and most impor­tantly will see more of them succeed.

Replace Volume-Discount pric­ing by Volume-Increasing pricing

Pric­ing is both a sig­nif­i­cant obsta­cle and oppor­tu­nity for savvy ven­dors and clients. Devel­op­ing a pric­ing strat­egy that bet­ter aligns value with price will help both to pro­vide and ben­e­fit from inno­v­a­tive IT applications.

So how should ven­dors approach a newly defined pric­ing strat­egy? We’ll take the social media exam­ple: price it with activ­ity met­rics cou­pled with increas­ing, not degres­sive, scale met­rics. In prac­tice, you would charge a price per user that actu­ally increases with the num­ber of active users inside the client’s orga­ni­za­tion. Looks wrong? Adopt your client’s point of view: if your deploy­ment is very suc­cess­ful, they will pay an expen­sive price but derive lots of value from it. Addi­tion­ally, if the deploy­ment needs to be phased to con­vince stake­hold­ers of the value poten­tial, they will also pay a match­ing price that will enable them to scale its use. Revers­ing the price struc­ture low­ers sig­nif­i­cantly the risk for the client, increas­ing the chances of a pilot happening.

A pos­i­tive exter­nal­ity of such a pric­ing strat­egy, at its peak for Enter­prise Social Com­put­ing offer­ings, is the cred­i­bil­ity and con­fi­dence about their prod­uct pro­jected by ven­dors. Nearly all are using argu­ments about how easy it is to engage employ­ees, how they will want to use it, col­lab­o­rate with each other, etc. So don’t limit your­self to the mar­ket pitch, embed this in your pric­ing and demon­strate your confidence.

Redefin­ing pric­ing habits is not easy but the rewards can be great

Ven­dors can do this by work­ing with their clients and defin­ing tar­gets for user activ­ity or user adop­tion. This will be eas­ier when your prod­uct is replac­ing a legacy appli­ca­tion, and more dif­fi­cult when it is truly innovative.

A good case study are the appli­ca­tions pro­vid­ing microblog­ging (or microshar­ing, in a word Twitter-like like Yam­mer (which just announced a on-premise ver­sion) or Present.ly) fea­tures for the enter­prise. The more users will use it, the more value the client orga­ni­za­tion will get out of it. In most orga­ni­za­tions how­ever, the value of a Twitter-like for cor­po­rate use will not be obvi­ous, and will slowly build up with time, as it spreads internally.

Yet, pric­ing is des­per­ately of a Volume-Discount type, mak­ing an after-pilot deploy­ment with a small group of early-adopters look very expen­sive per user (large com­pa­nies will com­pare it to the price per user for fully deployed appli­ca­tions like email or IM). Smart ven­dors will reverse the price struc­ture, offer orga­ni­za­tions the oppor­tu­nity to try out the new tech­nol­ogy, expe­ri­ence its value over time after a pilot, and scale up accord­ingly. They have to forgo imme­di­ate but short-term ben­e­fits, in order to get a chance to demon­strate their value added and reap the ben­e­fits as the client scales up its use.

Defin­ing the cor­rect strat­egy is not easy and will require time and efforts. Each side has of course oppo­site incen­tives for the def­i­n­i­tion of the ranges. Com­pounded with this, set­ting the tar­get in terms of active users for a suc­cess­ful deploy­ment in terms of user adop­tion will not be easy for truly inno­v­a­tive tech­nolo­gies. But there are many ways to imple­ment a good pric­ing strat­egy. Defin­ing ranges of user num­ber will likely be dif­fi­cult in many case: what should be a tar­get of active users, for Twitter-like appli­ca­tions, to define a suc­cess­ful deploy­ment? This can be mit­i­gated by set­ting tar­gets on user adop­tion rates. Stat­ing that the user base should grow by at least 10% from quar­ter to quar­ter or 3% from month to month would align clients and ven­dors very well. Incor­po­rat­ing in the con­tract that, say, a suc­cess­ful deploy­ment is 30% of all employ­ees, would enable to define a reward fee to the ven­dor if deploy­ment reaches 50% of active users. This will again match the value to the price and most com­pa­nies shouldn’t have a prob­lem with this.

The pos­si­bil­i­ties are truly infi­nite and have to be explored on a case by case basis, tak­ing into account the com­plete char­ac­ter­is­tics of a prod­uct. Let me dis­miss right away the most com­mon counter argu­ment for using Volume-Increasing price struc­tures instead of Volume-Degressive: ven­dors will lose a lot of value to small com­pa­nies that will never require to scale up. This is true, if no fences are in place. But it’s very easy to define at least 2 struc­tures based on the total size of the orga­ni­za­tion. For orga­ni­za­tions with less than 1,000 employ­ees, you apply Volume-Discount pric­ing. For more, Volume-Increasing. That may not be right for your prod­uct, but the point here is that you need to seg­ment your mar­ket, and then use this seg­men­ta­tion to apply dif­fer­ent structures.

In any case, pric­ing a prod­uct based on the num­ber of active users instead of seats, is the least a ven­dor can do, espe­cially if the soft­ware is deliv­ered as a service.

Deeply seg­ment­ing your total mar­ket then using inno­v­a­tive met­rics and fences to match price and value as closely as pos­si­ble is the sin­gle biggest oppor­tu­nity avail­able for both ven­dors and clients alike. Let’s use it.

You can also use the fol­low­ing slide deck to go fur­ther along this path:

How to price social enter­prises appli­ca­tions? Value and util­ity pric­ing through increas­ing price struc­tures

How to price social enter­prises appli­ca­tions? Value and util­ity pric­ing through increas­ing price struc­tures Why ven­dors and clients should develop and agree on reverse pric­ing schemes for all the “enter­prise 2.0” (mean­ing­less but broad buzz­word intended)? Increas­ing pric­ing struc­ture that increase the price as the num­ber of active users increases are far more efficient than cur­rent degres­sive pric­ing struc­ture, that dis­con­nect com­pletely value and cost for clients. This explains largely why, even as large enter­prises are express­ing inter­est, the mar­ket for this type of appli­ca­tions is not grow­ing nearly as quickly as needed and often antic­i­pated. This would also help the puz­zled ven­dors who won­der why, since their appli­ca­tion add so much value (they are right), only few large enter­prises are actu­ally will­ing to buy them at what seems a rea­son­able pric­ing (they are wrong). We explore here how ven­dors and their clients can cre­ate mutual value by agree­ing on increas­ing pric­ing schemes. Julien Le Nes­tour | Feb­ru­ary 09 | Use with this post (or not, but designed to!)| julien@macroprinciples.com | Cre­ative Com­mons Attri­bu­tion Non­Com­mer­cial Share Alike http://www.flickr.com/photos/alkalinezoo/2474735037/sizes/o/ A clas­sic degres­sive pric­ing scheme is the most com­mon struc­ture used by “enter­prise 2.0” ven­dors 1 Cur­rent sit­u­a­tion Aver­age cost for the orga­ni­za­tion of a new user active on the appli­ca­tion Price is usu­ally capped after a thresh­old Dol­lar scale $ 2 Aver­age Cost per user 0 10 50 200 1000 5000 10000 20000 40000 60000 N 100000 Num­ber of active users (absolute num­ber) Users scale (here in total num­ber of users) “Enter­prise 2.0” appli­ca­tion ven­dors have gen­er­ally adopted a clas­sic degres­sive pric­ing scheme: the price per user is decreas­ing as you buy access for more employ­ees. Julien Le Nes­tour | Feb 09 macroprinciples.com licens­ing Vari­a­tions like flat pric­ing may occur, but most usu­ally fall back to the same old and clas­sic degres­sive pric­ing scheme 2 Cur­rent sit­u­a­tion But of course you nego­ti­ate when you’re big and fall back to degres­sive Aver­age Cost per user $ 1 Flat price per user announced as a list price Aver­age Cost per user N 100000 0 10 50 200 1000 5000 10000 20000 40000 60000 Num­ber of active users (absolute num­ber) Some ven­dors choose to dis­play a flat price per user per period as a list price. But of course, it’s noth­ing more than clas­sic degres­sive pric­ing after a — usu­ally low — thresh­old. The same can be said for thresh­olds in num­ber of users (pay this for up to 10 users, than you pay this for up to 100, etc.). The main effect of these vari­a­tions is to dis­con­nect the mar­ginal and aver­age cost per user. The trend for the lat­ter remains the same how­ever. Julien Le Nes­tour | Feb 09 macroprinciples.com licens­ing Thanks to increas­ing returns dynam­ics, the aver­age value per user increases in scale for clients Cur­rent sit­u­a­tion Dol­lar scale: $ value extracted by the client orga­ni­za­tion Mar­ginal value for the orga­ni­za­tion of a new user active on the appli­ca­tion Aver­age Value per user N 0 10% 20% 30% 40% 50% 55% 60% 65% 70% 80% Num­ber of active users (% of total pop­u­la­tion) Users scale (here in % of total user pop­u­la­tion) All offerings falling in the “enter­prise 2.0” domain have some degrees of increas­ing returns dynam­ics: as more employ­ees start using the appli­ca­tion, the value they gain by using it increases. This can be any­thing from pos­i­tive net­work effect for basic appli­ca­tions to more com­plex scale effects for elab­o­rated offerings. To quote Umair Haque: “their mar­ginal pro­duc­tiv­ity increases in num­ber of con­nected users”. Since the indi­vid­ual pro­duc­tiv­ity of each indi­vid­ual start­ing to use the appli­ca­tion increases with scale, the mar­ginal and aver­age value of a new active user at the orga­ni­za­tion level is cumu­la­tively even more expo­nen­tial. Addi­tional sources: Umair Haque Julien Le Nes­tour | Feb 09 macroprinciples.com licens­ing The level of increas­ing returns scale effects depends on how well designed the appli­ca­tion is 2.0 RETURNS TO SCALE !”#$%&’(‘)*+,$ -(.$/+012(,$0′$3&-4+ Cur­rent sit­u­a­tion Com­bi­na­to­r­ial (Haque) The returns to scale of web and soft­ware appli­ca­tions vary accord­ing to their prop­er­ties. Increas­ing returns scale effects are now com­monly used by con­sumer and cor­po­rate appli­ca­tions. The type of returns achieved (their slope) depends on the prop­er­ties of the appli­ca­tions. Returns Expo­nen­tial (Reed) Poly­no­mial (Met­calfe) Scale We will 2.0 economies scale? Viral and net­work economies, because they How shoul­duse a simplified graphic ver­sion of the value curve, but ven­dors should strive to achieve the directly medi­ate users and/or peers, should real­ize polynomial-exponential returns best scale effects pos­si­ble within their offering. to scale. Dis­trib­uted economies, because they micro­me­di­ate the recom­bi­na­tion of plas­tic microchunks, should real­ize exponential-combinatorial returns to scale. Refer to Umair Haque’s excel­lent work (figure extracted from his pre­sen­ta­tion: The Age of Plas­tic­ity Edge Com­pe­tences and Net­work Eco­nom­ics 2.0) for a start­ing point: URL: http://www.bubblegeneration.com/resources/edgecompetences.ppt Source: Umair Haque, The Age of Plas­tic­ity Edge Com­pe­tences and Net­work Eco­nom­ics 2.0 Julien Le Nes­tour | Feb 09 macroprinciples.com licens­ing The size of the client’s orga­ni­za­tion impacts its value curve for absolute num­bers, not rel­a­tive num­bers Cur­rent sit­u­a­tion Dol­lar scale: $ value extracted by the client orga­ni­za­tion Small co Mid co Big co Aver­age Value per user 0 10 50 200 1000 5000 10000 20000 40000 60000 N 100000 Num­ber of active users (absolute num­ber) Users scale (here in total num­ber of users) Of course, the size of the client’s orga­ni­za­tion impacts the form of its value curve. The larger a com­pany is, the more extended its value curve will be. Note that when the scale used is the per­cent­age of users within the total employee pop­u­la­tion, then size is not a fac­tor and there is only one curve (see slide 4). Julien Le Nes­tour | Feb 09 macroprinciples.com licens­ing Value and cost are com­pletely mis­matched with a degres­sive pric­ing scheme while they should be as closely aligned as pos­si­ble! Ratio­nale for change Dol­lar scale: value extracted by the client orga­ni­za­tion $ Aver­age Value per user Aver­age Cost per user N 0 10% 20% 30% 40% 50% 55% 60% 65% 70% 80% Num­ber of active users (% of total pop­u­la­tion) Users scale (here in % of total user pop­u­la­tion) The price paid per user is decreas­ing as clients add users whereas the value extracted from each user increases with each new one brought on board. The mis­match is strik­ing and has sev­eral con­se­quences. Julien Le Nes­tour | Feb 09 macroprinciples.com licens­ing The incen­tives for large (hence risk averse) com­pa­nies to try a dis­rup­tive tech­nol­ogy are weak $ Ratio­nale for change Aver­age Value per user 1 2 3 Pilot pop­u­la­tion Deploy­ment being done Full deploy­ment pop­u­la­tion Pilot Cost per user N 0 10% 20% 30% 40% 50% 55% 60% 65% 70% 80% Aver­age Cost per user Num­ber of active users (% of total pop­u­la­tion) Large com­pa­nies will aim at a corporate-wide deploy­ment, the one max­i­miz­ing value. But they will approach it in a phased way: 1) First con­tact and nego­ti­a­tion of the long-term pric­ing for the full deploy­ment as well as punc­tual pric­ing for the pilot 2) Small scale pilot to test and mit­i­gate busi­ness, tech­ni­cal and user adop­tion risks 3) If pilot suc­cess­ful, expand to a pro­duc­tion deploy­ment Julien Le Nes­tour | Feb 09 macroprinciples.com licens­ing A degres­sive pric­ing scheme increases the cost of tran­si­tion­ing from pilot to pro­duc­tion for dis­rup­tive tech­nolo­gies $ Ratio­nale for change • Large scale deploy­ment • Small scale deploy­ment for user adop­tion • Low total cost • Unsus­tain­ably low ROI per user due to degres­sive pric­ing • Project at risk if does not scale quickly to lower cost per user and increase ROI to reap scale economies • High total cost • High ROI per user because of degres­sive pric­ing • Project at risk because the ramp-up period for user adop­tion will be long, while the cost paid and ROI planned assume full deploy­ment 40% 50% 55% 60% 65% 70% 80% Aver­age Value per user Pilot Cost per user N Aver­age Cost per user 0 10% 20% 30% Num­ber of active users (% of total pop­u­la­tion) After the pilot, 2 main strate­gies to deploy glob­ally: 1) (on the left) Start with a small group of users, usu­ally early adopters and for whom the busi­ness value is clear, then expand from this core 2) (on the right) Deploy glob­ally as quickly as pos­si­ble A degres­sive pric­ing scheme makes it very difficult to jus­tify either the total cost or the ROI per project. The more dis­rup­tive the tech­nol­ogy, the more difficult to demon­strate its benefits, the more such a scheme makes it more difficult to deploy. This helps explain he difficulty to get pilots for ven­dors and the risk averse nature of clients. Julien Le Nes­tour | Feb 09 macroprinciples.com licens­ing By switch­ing the price to align with the value, the total rev­enue for a ven­dor stays the same, even if reached at a different pace 1 Benefits $ Value 1) With degres­sive pric­ing, ven­dors are pric­ing out at small scale, while for­giv­ing most of the value at large scale 2) The total rev­enue with degres­sive pric­ing fol­lows the price (=cost) curve 3) If we switch the cost to align with the value, then the growth in rev­enue has a different pace, but the total rev­enue stays the same Pric­ing out For­giv­ing value N 0 10% 20% 30% 40% 50% 55% 60% 65% 70% 80% Num­ber of active users (% of total pop­u­la­tion) Cost 2 $ Value 3 $ Cost Value Total rev­enue with degres­sive pric­ing N 0 10% 20% 30% 40% 50% 55% 60% 65% 70% 80% Num­ber of active users (% of total pop­u­la­tion) Total rev­enue with increas­ing pric­ing Cost N 0 10% 20% 30% 40% 50% 55% 60% 65% 70% 80% Num­ber of active users (% of total pop­u­la­tion) Julien Le Nes­tour | Feb 09 macroprinciples.com licens­ing Ven­dors need to shift from few clients at full price (degres­sive pric­ing) to lots of clients at pro­gres­sively increas­ing prices (increas­ing pric­ing) 1 Benefits $ Rev­enue scale Degres­sive pric­ing Strat­egy: Expect large rev­enue streams from a few clients, don’t go if can­not get a full rev­enue stream right-away. If client wants to deploy pro­gres­sively, make it pay a dis­counted full price or par­tial but not dis­counted (can’t have both!). a Total rev­enue by client a) a very small num­ber of clients have done a full deploy­ment, pro­vid­ing large rev­enue streams b) a small num­ber of clients are pilot­ing the appli­ca­tion. The num­ber is small because of the planned difficulties to tran­si­tion. c) clients express­ing an inter­est, but not see­ing an ROI with a large enough prob­a­bil­ity, are stay­ing on the side­lines, due to the costs and uncer­tainty asso­ci­ated with a pilot Increas­ing pric­ing Strat­egy: Expect clients to start small-scope pilots to mit­i­gate poten­tial risks and demon­strate the value, then move on to a phased deploy­ment when the value has been demon­strated. Make it easy for them to jus­tify the project by giv­ing them a sta­ble ROI per user through­out the deploy­ment. Man­age a port­fo­lio of clients that are at vary­ing stages of their pilots and deploy­ment and increase rev­enue as they scale up. c N 0 100 200 300 400 500 600 700 800 900 Num­ber of clients … b c 0 100 200 300 400 500 600 700 800 900 Num­ber of clients … N 2 $ Rev­enue scale Total rev­enue by client a b a) a big­ger num­ber of clients are in full deploy­ment, but at avry­ing stages of it, pro­gres­sively deploy­ing the appli­ca­tion as their orga­ni­za­tion is get­ting used to it b) a large num­ber of clients are pilot­ing the appli­ca­tion, attracted by the very good cost/benefits/risks ratio c) clients express­ing an inter­est exper­i­ment with the basic ver­sions of the appli­ca­tion, or for very large prospects, kick-start an experiment/pilot with the vendor’s help licens­ing Julien Le Nes­tour | Feb 09 macroprinciples.com Util­ity pric­ing, ie pric­ing per active user, is nec­es­sary to allow a suc­cess­ful deploy­ment of a dis­rup­tive tech­nol­ogy $ 2 Price per user con­tin­u­ously Pric­ing Met­rics to avoid thresh­olds effects 1 Instead of charg­ing just 3 Aver­age Cost per user Aver­age Value per user different prices for 3 ranges N 0 10% 20% 30% 40% 50% 55% 60% 65% 70% 80% Num­ber of active users (% of total pop­u­la­tion) When deploy­ing a dis­rup­tive tech­nol­ogy like enter­prise social net­work­ing, it is impor­tant for the client to make it avail­able to all its employ­ees: which groups of employ­ees will rec­og­nize its value first is unknown, and you may not tar­get the cor­rect group if you do a tar­get deploy­ment. If charg­ing with thresh­old effects (x$ for 100 users, than y$ for 1000 users), the ven­dor makes artificial and unnec­es­sary dis­con­nects between cost and value. If charg­ing reg­is­tered users, the ven­dor does not charge for value but for its per­ceived poten­tial to deliver value, which can be badly wrong. Julien Le Nes­tour | Feb 09 macroprinciples.com licens­ing Note on pric­ing met­rics: why active users count is gen­er­ally more efficient Pric­ing Met­rics Active user pric­ing Active users activ­ity is often the best proxy for value. It should be auto­mat­i­cally tracked within the appli­ca­tion and at a high enough fre­quency (ie monthly or quar­terly, not just annu­ally). Activ­ity pric­ing not efficient Activ­ity pric­ing aims at match­ing value and price exactly. It is very difficult to define activ­ity met­rics that match value exactly how­ever, and gen­er­ally the dis­con­nect is too large to be used efficiently. Exam­ple: enter­prise search appli­ances pric­ing per doc­u­ment indexed fall in this trap obvi­ously. Most com­pa­nies have poor archiv­ing prac­tices, keep­ing obso­lete doc­u­ments on the net­work. Charg­ing to index those doc­u­ments (that can rep­re­sent a large por­tion of the total doc­u­ments) sim­ply increase cost with­out increas­ing value. Activ­ity pric­ing too uncer­tain for dis­rup­tive tech­nolo­gies Another rea­son why activ­ity pric­ing is a sec­ond best to active users pric­ing is the difficulty to define tar­gets for dis­rup­tive tech­nolo­gies. Search is known. Take the appli­ca­tions deliv­er­ing Twitter-like capa­bil­i­ties to the enter­prise. The best would be to price by usage, that is, by mes­sage. But how do you define the “nor­mal” usage to set your prices ? No one knows. Price it per active users how­ever, and you do cap­ture the value rec­og­nized by the employ­ees, since they will con­nect only if they find value in its use. Julien Le Nes­tour | Feb 09 macroprinciples.com licens­ing The cost/benefit ratio of Increas­ing Pric­ing for small com­pa­nies is too low, Degres­sive Pric­ing is adapted here $ Big co Mid co Small co Aver­age Value per user Seg­men­ta­tion The mech­a­nisms of value are the same for small com­pa­nies. Look­ing at the value in terms of the pro­por­tion of total employ­ees bring the same results. N 0 10% 20% 30% 40% 50% 55% 60% 65% 70% 80% Num­ber of active users (% of total pop­u­la­tion) $ Small co Mid co Big co Aver­age Value per user Looked at it in terms of absolute users, how­ever, the cost/benefit of imple­ment­ing increas­ing pric­ing is too low for ven­dors. For small and some­times medium com­pa­nies, the best strat­egy is to keep degres­sive or flat pric­ing. A thresh­old then needs to defined by the ven­dor to deter­mine when switch­ing from degres­sive pric­ing to increas­ing. This needs to be based on the total num­ber of employ­ees in the client’s orga­ni­za­tion. 0 50 1000 10000 40000 100000 N Num­ber of active users (absolute num­ber) Julien Le Nes­tour | Feb 09 macroprinciples.com licensing
  • http://bluekiwi-software.com Arnaud Pou­jardieu

    Bon­jour Julien
    I fully agree with your point of view related to ESN pric­ing model
    Chang­ing pric­ing model and habits is tough. Those who will suc­ceed in this chalenge will get a more bal­anced rela­tion between ESN provider and clients. This will cre­ate more Win win con­di­tions which is manda­tory for long term mutual valu­able rela­tions oppor­tu­nity.
    I am work­ing at blueKiwi. Are you ready , for bench­mark­ing this model together within Schlum­berger?
    Will be please talk­ing with you

  • http://www.macroprinciples.com Julien Le Nestour

    Hi Arnaud -

    Thanks for your com­ments. I am not blog­ging as an employee here so I will be in touch pri­vately. Don’t want to cre­ate any ambiguity ;-)

    Best regards,
    - Julien

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  • http://attensa.com char­lie

    Julien, thanks for writ­ing this. It sum­ma­rizes nicely a crit­i­cal strate­gic issue for both the enter­prise cus­tomer and the ven­dor. As you point out find­ing this align­ment is crit­i­cal to suc­cess­ful rela­tion­ships in the long term. Pilot­ing social appli­ca­tions is and inter­est­ing exer­cise given the nature of the value curve. Artic­u­lat­ing hard ROI from smaller pilots and then extrap­o­lat­ing that for­ward to big­ger user pop­u­la­tions is crit­i­cal. Any fur­ther thoughts on this by you or your read­ers would be welcome.

  • http://www.qitera.com carlo

    Hi Julien,

    thanks for this excel­lent piece of analy­sis. At my com­pany Qit­era that offers a enter­prise social search plat­form (http://www.qitera.com/enterprise) we are cur­rently defin­ing our new pric­ing shemes and your arti­cle brings in some very well-thought perspectives.

    I am also senior advi­sor at IT-research firm Exper­ton Group and rec­om­mended your post to the read­ers of our new blog. http://experton-group.blogspot.com/2009/02/ente…

    regards et à bien­tôt
    Carlo

  • Jon Hus­band

    I’ll com­ment more later, but for now …

    In gen­eral, the argu­ment you have set out has artic­u­lated en brouil­lon the think­ing I have been doing about what I call ROII (Return on Invest­ment in Inter­ac­tion). For that I thank you.

    Re: Adopt your client’s point of view: if your deploy­ment is very suc­cess­ful, they will pay an expen­sive price but derive lots of value from it. Addi­tion­ally, if the deploy­ment needs to be phased to con­vince stake­hold­ers of the value poten­tial, they will also pay a match­ing price that will enable them to scale its use. Revers­ing the price struc­ture low­ers sig­nif­i­cantly the risk for the client, increas­ing the chances of a pilot happening.

    A pos­i­tive exter­nal­ity of such a pric­ing strat­egy, at its peak for Enter­prise Social Com­put­ing offer­ings, is the cred­i­bil­ity and con­fi­dence about their prod­uct pro­jected by ven­dors. Nearly all are using argu­ments about how easy it is to engage employ­ees, how they will want to use it, col­lab­o­rate with each other, etc. So don’t limit your­self to the mar­ket pitch, embed this in your pric­ing and demon­strate your confidence.

    I think that this is essen­tially the inverse of (for exam­ple) a $50 mil­lion dol­lar SAP implementation.

    Which I think speaks to tim­ing and atten­tion scarcity. SAP for me is (still) an exam­ple of a tran­si­tion tech­nol­ogy, as the evo­lu­tion of IT applied to busi­ness and work processes began the major move from paper to infor­ma­tion sys­tems in a real and per­va­sive sense. If you think about it, it wasn’t really that com­plex .. take exist­ing processes, align them hor­i­zon­tally instead of ver­ti­cally, strip out obvi­ous redun­dan­cies (every­one remem­ber the “Spot the Waldo” reengi­neer­ing stuff ?), and then pour elec­tronic con­crete (SAP sys­tem) over it.

    Now we are mov­ing into col­lab­o­ra­tion appli­ca­tions lay­ered over a dense-and-deep IT infra­struc­ture (let’s leave ERP sys­tems out of this aspect for now), appli­ca­tions that con­sist of stitch­ing together var­i­ous web tools and web ser­vices (as a gen­er­al­ity) that lay on top of the denser, more “per­ma­nent” data­bases and engines. These appli­ca­tions ands ser­vices are becom­ing both more open and more inte­grated all the time, to the point where through “open” APIs peo­ple can plug the tools they like using into larger appli­ca­tions and sys­tems. As the con­cept of “cloud com­put­ing” evolves, so too will the mix-and-match personalisation.

    The for­mer (and cur­rent) pric­ing mod­els assumed amor­ti­za­tion of invest­ment over time in some­thing more-or-less per­ma­nent (at least, assumed to be for the pur­poses of ROI hurdles).

    With large-scale (and over time grow­ing) par­tic­i­pa­tion and inter­ac­tiv­ity, the notion of value obtained and cre­ated changes, as you have pointed out.

    I’ll re-read and think, and come back when I feel I can talk cogently about ROII.

  • http://www.macroprinciples.com Julien Le Nestour

    Hi Jon, many thanks for the already insight­ful com­ment, eager to read more :-)

    Yes, ROI is no longer a mean­ing­ful met­ric. What amazes me now is how many peo­ple are judg­ing a tool based on its “fea­tures”, which is an even less rel­e­vant con­cept to judge IT offerings.

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  • Sibs

    Juliene,

    Great arti­cle, thank you for shar­ing. I agree with your point of view 100%. The net­work effect of social com­put­ing in the enter­prise is a great way of artic­u­lat­ing the argu­ment of vol­ume increas­ing pric­ing. I think there are two bar­ri­ers to address, how­ever, by ven­dors and ven­dors in con­sul­ta­tion with their clients. 1) Bal­anc­ing those ele­ments of a solu­tion that may be con­strued by orga­ni­za­tions as more social-social than social-work and 2) Ensur­ing that the client marketing/champion is doing a good enough job to drive adop­tion. From our expe­ri­ence deploy­ing our next gen­er­a­tion direc­tory solu­tion (http://gtec.innovapost.com/), these two issues are a chal­lenge to a vol­ume increas­ing pric­ing strategy.

    For #1, with many social appli­ca­tions there are often fea­tures and func­tion­al­ity that don’t have a hard link to busi­ness pro­duc­tiv­ity. I’m an advo­cate of 2.0 in the work­place as I believe there are pro­duc­tiv­ity (see my whitepa­per Beyond Func­tional Con­tri­bu­tion via the link above) and employee engage­ment ben­e­fits to be reaped, but we do have to be care­ful because some solu­tion ele­ments are, and will be, used for social-social pur­poses. If the solu­tion has an abun­dance of fea­tures that drive social-social behav­iour and attract users as a result, it’s a tough pill to swal­low for orga­ni­za­tions to pay more because the orga­ni­za­tional value propo­si­tion under these cir­cum­stances because more ten­u­ous. Those of us in the Enter­prise 2.0 space would still main­tain there is value, and I am one of them, but not all of our cus­tomers will.

    For #2, I think we all agree that enter­prise 2.0 is largely a cul­tural par­a­digm shift about the nature of work and the view of employee behav­iour. So deploy­ing these solu­tions in the enter­prise requires the enter­prise to roll up its com­mu­ni­ca­tions, cul­ture change, and mar­ket­ing sleeves and pro­mote the inter­nal solu­tion like they would their lat­est prod­uct launch. As a ven­dor, we need to help guide these efforts as they will directly impact the use of the solu­tion. If we don’t pro­vide clients with any help, but we want vol­ume increas­ing pric­ing, we’re not doing our­selves any favours.

    Just a few ram­bling thoughts as I read your article.

    Warm regards,

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  • http://www.club-penguin.org/ Club Pen­guin Cheats

    It sum­ma­rizes nicely a crit­i­cal strate­gic issue for both the enter­prise cus­tomer and the ven­dor. As you point out find­ing this align­ment is crit­i­cal to suc­cess­ful rela­tion­ships in the long term. Pilot­ing social appli­ca­tions is and inter­est­ing exer­cise given the nature of the value curve.

  • http://freekidsgames.vox.com/ Kids Games

    Inter­est­ing assess­ment. Devel­op­ing a pric­ing strat­egy can always be a source of con­tention for com­pa­nies. You lay out a good out­line to follow.

  • http://freekidsgames.vox.com/ Kids Games

    Inter­est­ing assess­ment. Devel­op­ing a pric­ing strat­egy can always be a source of con­tention for com­pa­nies. You lay out a good out­line to follow.