Procurement Data Integration: A crucial step in digital transformation

data integration

Spend Matters welcomes this guest post from Sergii Dovgalenko, CPO at JSC Ukrainian Railway.

According to the International Data Corporation, 10% of digital data is structured, leaving 90% unused, unstructured and hidden.

During these times of Industry 4.0, many companies have substantially progressed on the path toward digital transformation. Fellow procurement colleagues operate their new shiny source-to-contract suites, P2P and SRM tools. However, one critical aspect of digitalization sometimes remains forgotten or insufficiently addressed.

The procurement value chain spreads well beyond the S2C cycle — it starts from planning and goes all the way to supplier performance and risk management. Even if your chief architect is a genius and managed to build the fully integrated digital pipeline of planning, budgeting, sourcing, contracting, material management, P2P and SRM modules, where tasks freely flow from one section to another, the data integration may remain a challenge.

Defining procurement data integration

First, let’s provide the definition: Data integration is the process of combining data from different sources for analysis, business intelligence, reporting and feeding into other digital systems.

In e-procurement, each distinctive module consumes, generates and feeds loads of data. The free flow of data is not a given — sometimes, planning and budgeting happen in finance systems; PRs come from end users randomly to initiate the sourcing process (sometimes not even PRs but emails!); sourcing process ends with a supplier award; contract data entry is manual with just a reference to the sourcing project ID; contract-to-pay cycle jumps between different systems (PO in e-procurement, GRN in Material Management, invoicing and payment in AP module.) Besides the lack of process management, such patchwork installations generate buckets of disintegrated data that needs to be manually cleansed, enriched and analyzed even for such standard tasks as cycle-time measuring or spend analysis.

More coverage: Check out our SolutionMap data, which shows where 77 procurement technology vendors rank against each other.

The process of data integration is far more complex than what’s been described above. The e-procurement suite is just a link in the supply chain data network. Finance systems are natural sources of data for procurement analysis, as their data are structured similarly for the ease of exchange within the ERP environment. For example, the AP module will be the reference source of data for spend analysis.

Further complexity will be observed across other internal systems, where the data format and presentation are different from the ERP one. From my experience in the aviation industry, procurement can obtain useful info from Catering on consumption, spare-part planning inputs from MRO, cash-flow projections from Treasury, digital assets (e.g., licenses) from IT, and more. However, even accessing this data from an IT security perspective could be a challenge.

The least visible and utilized procurement data is out there on the supplier side. No need to explain how useful that data could be if there were the simplest integration between your systems and ones of your partners.

Besides supplier systems, multiple external systems could be integrated to improve the business intelligence and analytical capabilities of procurement — supplier financial and risk analysis, global and domestic economic reports and forecasts, open and subscription-based price databases, commodity indexes, etc.

Managing data feeds

To sort out this “spaghetti-bowl” of internal and external data feeds, procurement can use a few standard solutions:

  • Manual extraction and analysis or so-called Common Data Interface. This integration happens on the screen of a procurement analyst, who opens multiple windows with different reports and tries to reconcile and find some logical connections and patterns. Unfortunately, for many companies that claim to have undergone digital transformation, this is how far the data integration goes.
  • Uniform Data Access is the integration of data based on a similar format, e.g., between procurement and finance systems.
  • More sophisticated types of integration assume the understanding of the importance and complexity of the subject and preparedness to invest in appropriate solutions. Data Warehouse stores data from multiple applications and platforms and can be used as a data lake, from which it is extracted, analyzed and packaged in custom reports by the specialized software.
  • Application-based integration is an automated search, extraction and processing of data by a dedicated app.
  • In technologically advanced companies, integration occurs on the Middleware level. Internal and external systems communicate via the dedicated software layer, and the data ingestion and format is standardized and usable across all connected platforms.

The experience of many companies that invested in best-in-class procurement and ERP platforms still indicates the lack of attention to data integration. This leads to procurement operating automated workflows but not utilizing the full potential of analytics and business intelligence, and highly sophisticated systems producing arrays of dark data that is never going to be used. As data is called the “oil of Industry 4.0,” companies need to utilize it as consciously and effectively as they are managing their fossil fuels and energy.

We are pleased to say that Spend Matters will be hearing more from Sergii Dovgalenko next month when we talk to him about his experiences of digital transformation within his organization.

 

Disclaimer: The opinions expressed are those of the author and do not necessarily reflect the official position of Spend Matters.

Share on Procurious

Discuss this:

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.