Why Data Quality should be a New Year’s Resolution for Manufacturers in 2023
As we embark on another new year, any organization that is planning to invest a significant amount of effort and money to implement or adopt SAP technology knows too well about the importance of the data quality prerequisite. But with S/4 HANA, it is becoming more and more a firm non-negotiable.
Whether you are preparing for a full-scale data migration programme or new to SAP entirely, all of your efforts will be likely be in vain without a follow-on data governance framework going forward to ensure data remains a company asset and not enemy number one.
If we have learnt anything from the ghosts of ERP project pasts, high (actually, very high) on the list of overall prioritise needs to be data readiness. In our opinion, preparatory and planning activities can never start soon enough and well before anyone gets stuck into the detail of those terabytes of legacy company data! New Years Resolutions are never easy to stick to, but in this blog we aim to demonstrate why this should be one for manufacturers looking to navigate 2023 successfully and how to make it a resolution that sticks.
What’s the current state of Data Governance in 2023?
As part of RISE with SAP, many customers are now in a position to start considering an age-old ERP conundrum of when and how to deal with the master data that is so critical to the success of their business initiative. Many customers are now facing up to stark questions such as.
“In reality, can we really continue to ignore solid data management practices whilst faced with such a critical business transformation”
“Notwithstanding our ETL efforts to support our S/4 HANA programme, how do we continue the momentum with the transition towards upkeeping data requirements going forward”.
There is no question, the standard SAP MDG solution out-of-box provides a robust and comprehensive data model for material master data governance in isolation and ultimately deserved careful software evaluation time and effort. However, secondary SAP master data domains such as the bill of material, production routing/recipe and SAP SCM standalone data objects are becoming ever more critical to ensuring the full lifecycle of data management from a supply chain perspective in 2023.
Will manufacturing data quality be easier or harder in 2023?
Constant real-world fluctuations are forecasted to persist throughout 2023 and into 2024. The rise of new digital industrial technology, known as Industry 4.0. “is a transformation that makes it possible to gather and analyse data across machines and equipment, enabling faster, more flexible, and more efficient processes to produce higher-quality goods at reduced costs.” This tells us that data will be even more crucial as we have more and more integration and therefore potentially different sets of data with multiple ‘so-called sources of the truth’.
Secondly, Data analytics, which has been completely overtaken by technologies like artificial intelligence (AI) and machine learning (ML) will need to be underpinned by sound underlying data management practices within the enterprise. This especially holds true for early adaptors of PMRP algorithms.
Specifically in the context of SAP S/4HANA and manufacturing, the introduction of EWM and APO modules within the core solution stack means a growth in master data requirements management for ERP business processes. The traditional viewpoint of a single material master business object is no longer valid for those who activate the embedded offerings of EWM and APO.
In the pursuit of this holistic approach towards excellence in SAP supply chain master data management, many clients face further embarking on either some form of subsequent joint PLM data initiative or solution extension to their existing SAP MDG platform. This then seeks to provide a complete governance model for such critical, secondary supply chain data domains. However, the total cost of ownership of such solutions and the complexity of developing, maintaining and integrating these domains into border master data management workstreams quickly begins to escalate into a costly and time-consuming IT-driven initiative.
For SME’s, the level of investment required in order to achieve this often becomes difficult to justify and as a direct consequence, data processes often become more fragmented than from the very outset. From our experience, the value case for further investment in MDM technologies for manufacturing enterprises in particular often lies in streamlining business processes across a number of different supply chain data objects. These business processes often extend beyond the scope of centralised master data teams and therefore, tooling that enables both a wider coverage of application-specific data objects and accompanying decentralised workflow measures becomes critical to achieving the overall MDM vision.
Why is data quality essential in 2023?
Data quality is important, now more than ever for both internal and external users helping make better decisions and gaining insight into key events and processes. Data quality is defined within an enterprise and should set an expectation of its accuracy, validity, completeness, and consistency across all lines of business and those inherent business processes.
What issues are customers still experiencing from poor data quality?
Without stating the obvious, data will impact and touch almost everything so the impacts of poor data quality will hurt your business however big or small, especially if you manufacture.
Data quality is a living organism, flooding throughout your data manufacturing & supply chain. In order to bring data quality to life, enterprises need an information intelligence & data governance platform in place. incorrect product data, component data, recipes, etc., have huge repercussions. Even before Manufacturing starts, incorrect data in new product development can stop a great innovative product from even getting to market. From forecasting through to manufacturing itself, measuring the quality of goods produced is so very important. If data is not of a high quality it can lead to multiple impacts which will affect your bottom line and customer base.
The root cause of a supply chain breakdown is often the result of inaccurate or incomplete reference data. Specific examples include;
- Failed or late deliveries
- High manufacturing throughput time.
- High levels of working inventory.
- Incomplete quality management data.
How do customers typically resolve any issues in data quality?
Data remediation is often reactive, in response to any of the above examples of a supply chain breakdown. This has the potential to impact areas such as product compliance and overall customer satisfaction and may only be fed back to the business at this point.
Often as not, resolving data quality issues are not possible – it’s just too late. A lot of organisations try to introduce data quality systems and processes to analyse data (such as profiling) but sometimes miss the root cause. Many businesses today fix data retrospectively (after the horse has bolted) and we would say that ‘data analysis’ is only part of the solution. Some key points where enterprises have succeeded in this complex topic are areas such as:
- Understanding/reviewing the data
- Defining their standards of data
- Cleansing data,
- The one most business miss is the ‘understanding of their data flow/process. This especially in regard to data creation, data change and data extension. This in turn, analyses the low of data and the standards by which systems interacting with each other and involving the right people at the right time
What does a journey to better data quality look like?
One of the key things is bringing data and processes together. Understanding the standards that are applied during that process. Once you have this, you can run a high-quality data lifecycle and use that same standard to analyse and cleanse data and enrich the data standards.
As the momentum of S/4 re-implementation in particular gathers pace, a comprehensive data strategy will be required in order to establish common rules and processes to manage data across the entire organization. Solutions will perform a part of this, but an approach of needs must for certain SAP data domains such as the mandatory business partner adoption, have an overall weighting on the likelihood of what can be achieved in the overall project timeframe.
In our opinion, customers should use the opportunity presented by a significant event such as a S/4HANA re-implementation, upgrade or migration project to lay the ghosts of data programme management past finally to rest in some capacity!
Now more than ever is the perfect time to reach out to solution providers alike to understand innovations for the journey ahead.
What is Maextro and how can it help data quality?
To address the above, Bluestonex has developed a new suite of Maextro object extension frameworks that seeks to address the streamlining of SAP supply chain master data objects. Maextro is a no-code data quality and data process solution. Its key differentiator is for all users that touch data to be involved in the process. Rules, intelligent workflow, analytics and a simple yet powerful user interface move data ownership back to the people that should own the data & its quality (and by that, we don’t mean IT).
Born initially out of the requirements of the FMCG industry, this solution allows businesses to create both linkages and dependencies between SAP supply chain data domains on a single centralised SAP platform. For example, as a master data steward for supply chain data, the solution could provide an end-to-end framework for managing the introduction of a new finished goods product, in conjunction with an associated manufacturing bill of material, routing/recipe document data and all embedded SCM product data attributes newly introduced as part of the SAP S/4HANA application package.
By developing a pre-defined framework for flexibly creating object linkages and dependencies, the solution also retains its capability to administer any linked data objects in isolation. For example, the very nature of the bill of material data object in SAP typically requires the administration of a number of periodic, value adding data activities. One example being the correct component inventory quantities being continually reflected in line with production consumptions/variances.
Which areas of the business is Maextro good for?
Maextro will cover anything and everything that touches SAP software but more so SAP ERP. ERP runs your business (product, manufacturing, financials, sales, procurement, HR records, customers, vendors and many more) so you need a quality, governance and process tool to allow the systems and users (both IT and end users) to interact with the data to ensure there is that one single source of truth whilst applying rules and governance at each step of the lifecycle.
Are customers notified about data quality issues?
Again, right now, many customers find out after the event. In the Maextro world, rules are applied real-time during processing of data. Users, stakeholders, and owners (or all three) are notified when rules & processes are not followed or not adhered to. So rather than find out after the event, Maextro will alert users in real-time.
What’s being added to Maextro to help customers in 2023?
As an innovation partner, our research & development cycle never stops. Data is everywhere therefore data quality, data process and governance are now more important than they’ve ever been which means our analysts and developers have been working hard.
Maextro is evolving at a speed of knots, we have created new intelligent technology such as machine learning, risk and compliance capabilities and have even launched Maextro into operational processing. By this, we mean that Maextro is a process, governance and quality framework for data. Data is everywhere and everything. You don’t just create a data object (product, recipe, customer-vendor etc) and forget about it as these are then consumed within an operational process (sales, order, production order etc).
Maextro’s intelligent framework can now monitor and manage this operational layer. With recent releases of SAP Business Technology Platform, Maextro has many User Interfaces from SAP UI5 (responsive design across all devices) to chatbots and iRPA (Use of email and excel) so that different types of users can interact with data without the complexity of screens typical data solutions use.
As integration is in such high demand Maextro has low code integration points and can consume API’s. Again, useful for checking data that is available to enterprises.
For interacting with business partners (customers and vendors & their products) we introduced a business partner portal for governance and quality allowing Business Partners to interact with their data in real-time and Maextro again controls the flow, the rules and the governance before approval of data.
For customers who have already invested heavily in MDG and PLM technology and want to continue to sweat these assets for the foreseeable future, the Maextro extension framework could serve capability as the governance tool for secondary data object only at the local (plant) level or supplement gaps in existing SAP and non-SAP PLM handover to manufacturing business processes. With this approach, data is still administered where it is fundamentally utilised to support business transaction throughput and by the business representative who best understand it.
Five key considerations before embarking on a master data management programme for manufacturing.
To conclude, 2023 will be a challenging year for manufacturers but data challenges also present a number of opportunities. To leave you with the best mindset for looking at your current standards of data quality and what to aim for with an MDM program, here are 5 key considerations before embarking on a master data management program:
Will this enable a single source of truth?
MDM for manufacturing organisations must bring together processes and data silos spread across disparate PLM, ERP and MES systems in a scalable and structured manner. The overall vision is often to minimize the complexity of the data supply chain to the retailer/distributor, supplementing existing investments made in PLM, ERP and MES technology.
Balancing global and local
For the vast majority of manufacturers, centralization of master data management related business activities is only applicable to a finite number of data attributes. For example, localisations of product inspection characteristics due to regulatory compliance is often best handled by data stewards in the respective regions of specialisation. MDM solutions therefore require the capabilities to handle responsibility for data attributes at a granular/scalable level(s).
Providing the right data at the right time
Product ranges are often proliferated, and data supply confounded by shortening time-to-market expectations. Sound MDM practices enable NPI/NPD to realistically achieve such expectations and collaborate efficiently with the wider business teams responsible for data attribute maintenance throughout the whole data lifecycle.
Maintaining regulatory compliance
A clear segregation of duty between data administrators, stewards, and approval steps, dovetailed with the respective data models provides a robust and auditable MDM framework for industry compliant manufacturing methods to be defined.
Underpinning industry 4.o requirements
Automated productive environments are critically dependent on being fed ”sound” underlying master data. The movement towards cloud technology at the shop floor level has only exacerbated data requirements and will continue to grow as more manufacturing steps are brought online.
As we have mentioned above, there’s a lot happening with Maextro this year. Now is a perfect opportunity to quash any lingering or impending data gremlins before they have any potential to impact your S/4 programme. If you would like to know more about any existing or new features, we offer free demonstrations for enterprises to get hands-on. If you would like to know more about how Maextro can help your enterprise grow in 2023 and beyond, sign up for a free Maextro demo here.
If you would like to read more about the challenges manufactureres will be facing in 2023, check out our blog on 9 trends manufacturers will face in 2023 here.
WWrite a Comment