Sec­ond of a two-part Guest Con­trib­u­tor series.

In an ear­li­er arti­cle, Allan Coul­ter of IBM explained the ratio­nale for clean core and the approach enabled through IBM, SAP, and ecosys­tem solu­tions like Syni­ti. Here Coul­ter is joined by Rex Ahlstrom, Syni­ti Chief Tech­nol­o­gy Offi­cer, to dig deep­er into the role of data as an inte­gral part of clean core solu­tion and how to rethink its val­ue to the over­all intel­li­gent trans­for­ma­tion journey.

His­tor­i­cal­ly, data has been seen large­ly as a tech­ni­cal con­sid­er­a­tion with a focus on object-based data qual­i­ty, tech­ni­cal ​“lift-and-shift” migra­tion for align­ing the tar­get attrib­ut­es to sup­port the trans­ac­tion­al exe­cu­tion in SAP, or trans­ac­tion­al integri­ty through mas­ter data man­age­ment (MDM) solutions.

The real­i­ty, how­ev­er, is that data is a busi­ness problem.

The crit­i­cal nature of this can’t be under­es­ti­mat­ed. As most orga­ni­za­tions have expe­ri­enced, many post-go-live migra­tion chal­lenges result from data integri­ty issues. That’s why com­pa­nies like IBM trust Syni­ti solu­tions to turn this prob­lem into an oppor­tu­ni­ty for growth.

Fast for­ward to today, where we con­stant­ly hear that data is the ​“new oil,” the most impor­tant com­mod­i­ty in our client orga­ni­za­tions. As a result, we see a new focus on trans­form­ing data from a by-prod­uct of trans­ac­tion­al excel­lence into one that pow­ers the shift to the intel­li­gent enter­prise. The IBM Clean Core offer­ing empha­sizes code and data mod­ern­iza­tion to make SAP solu­tions sim­pler and smarter through data-dri­ven AI insights. Embed­ded in our phi­los­o­phy and approach — backed up by IBM and Syni­ti soft­ware solu­tions — is the abil­i­ty to solve data qual­i­ty and rel­e­vance chal­lenges as part of the Clean Core approach for SAP implementations. 

The Shift to Intelligence

As a leader in AI and advanced ana­lyt­ics, IBM has seen the ben­e­fits of mov­ing from tra­di­tion­al ERP approach­es to Intel­li­gent Enter­prise solu­tions – redefin­ing the user expe­ri­ence in the shift from man­u­al to dig­i­tal (intel­li­gent work­flow) processes.

Iden­ti­fy­ing data cat­a­logues and knowl­edge graphs are foun­da­tion­al to enabling this AI trans­for­ma­tion. How­ev­er, one of the biggest hur­dles in this shift is that the insights aren’t trust­ed because of low-qual­i­ty data.

To achieve opti­mal insights, we need­ed a high­er empha­sis on both data qual­i­ty and data stan­dard­iza­tion across the data foot­print, shift­ing to a more uni­fied data mod­el approach.

Data qual­i­ty isn’t just about data dedu­pli­ca­tion. Instead, focus on data con­sis­ten­cy, true data qual­i­ty, and what’s need­ed to help improve busi­ness out­comes. There’s tremen­dous val­ue in get­ting the data right. It’s not just for migra­tion process­es; it’s key to achiev­ing actu­al busi­ness ben­e­fits and goals. 

Get­ting It Right Matters

Accel­er­at­ing intel­li­gent enter­prise trans­for­ma­tion, dri­ving con­tin­u­ous inno­va­tion, and achiev­ing busi­ness out­comes must start with a clean and qual­i­ty data foun­da­tion. Under­stand­ing the qual­i­ty state and com­plete­ness of data pri­or to the move to, say, SAP S/4HANA® is key to a suc­cess­ful trans­for­ma­tion effort. In addi­tion, right­siz­ing data will help opti­mize per­for­mance and poten­tial­ly reduce spend on need­ed cloud infrastructure.

Typ­i­cal­ly, if the project is approached as a tech­ni­cal exer­cise, you get poten­tial­ly a team focused on a tech­ni­cal solu­tion. They may use an Extract, Trans­form and Load (ETL) tool. The prob­lem is that all the knowl­edge and learn­ing is buried in the ETL. It’s not reusable in any way; there’s no doc­u­men­ta­tion for it. You’re basi­cal­ly in the same state as you were before you migrat­ed – and none of that invest­ment is being car­ried forward.

It’s a missed oppor­tu­ni­ty. Even if you are not ready for AI just yet, this is the best time to pre­pare your data for the future. 

Trans­form Dig­i­tal Transformation

Syni­ti and IBM recent­ly announced the IBM Data Readi­ness Assess­ment with Syni­ti Knowl­edge Plat­form to help accel­er­ate dig­i­tal trans­for­ma­tion for their joint cus­tomers prepar­ing to tran­si­tion to SAP S/4HANA. Through bet­ter data qual­i­ty assess­ment, con­ver­sion, process opti­miza­tion, and code/​infrastructure mod­ern­iza­tion, this solu­tion helps advance the goal of accel­er­at­ing dig­i­tal trans­for­ma­tions and dri­ving con­tin­u­ous inno­va­tion by begin­ning with a clean and qual­i­ty data foundation.

The offer­ing enables joint cus­tomers to size the ser­vices and time required and assist with right-siz­ing data to opti­mize per­for­mance and pos­si­bly low­er the bud­get spent on need­ed cloud infra­struc­ture. Joint cus­tomers ben­e­fit from one plat­form that helps accel­er­ate projects, even those already in process, and that reduces project risk. 

The IBM Data Readi­ness Assess­ment with Syni­ti Knowl­edge Plat­form^[1] is an end-to-end, com­pre­hen­sive solu­tion that reuses all the con­tent and rules gen­er­at­ed with­in the plat­form to help accel­er­ate and auto­mate the migra­tion. This unique solu­tion con­nects data qual­i­ty to true busi­ness out­comes using hun­dreds of pre-built data qual­i­ty reports and dash­boards that iden­ti­fy cost sav­ings, cash flow, and P&L improvements.

Next Steps

The clean core phi­los­o­phy is now accept­ed. IBM has been lead­ing the charge in extend­ing this from Code to Data and Process Mod­ern­iza­tion. By work­ing in col­lab­o­ra­tion with ecosys­tem part­ners like Syni­ti, insights be achieved while exe­cut­ing data mod­ern­iza­tion. Whether start­ing or amid an Intel­li­gent Enter­prise jour­ney, explor­ing the oppor­tu­ni­ties pro­vid­ed in mod­ern­iza­tion of your data will set the right foun­da­tion for the shift to intelligence. 

Rex Ahlstrom is Chief Tech­nol­o­gy Offi­cer at Syni­ti and Allan Coul­ter is IBM Con­sult­ing Glob­al Chief Tech­nol­o­gy Offi­cer for SAP Services.

[1] https://​www​.syni​ti​.com/​n​e​ws/sy…