execon partners publish article “Does your strategic procurement have the time to think strategic?”

Many companies advertise big data solutions as “the next thing” in the C-suites. But how does an implementation look like and how can it concretely help in business life and create tangible value for your company? In this article published on GoINPHARMA™ execon partners´Lorenzo Nanetti and Lorenzo Formiconi expand on the role of big data solutions in procurement in pharma, how they can reshape the business processes, and which are the pitfalls that a big  data transformation implies.

During the last years the growing pressure on margins from the patent cliff and the price squeeze from regulators led the pharma industry to search for opportunities beyond R&D and sales that are at the core of its business model. One of the areas that most gained in terms of management attention is Procurement. Since the economic crisis several pharma companies are in fact onboarding additional procurement talent, pushing more strategic sourcing projects on their top management agendas, and setting bolder targets for cost reductions. While the effort is clearly paying off, there are still some hurdles that prevent the procurement departments in pharma to fully exploit their potential.
One of these is the amount of data that is required within a procurement department to function well and the level of manual effort at which this is processed. In fact, this appears to be quite high: a recent survey of execon partners shows that sourcing professionals in pharma invest up to 50% of their working time in transactional activities such as collecting and updating documents, manually processing and reformatting data, or creating and filing reports, with limited time left for true strategic activities such as monitoring supplier markets, identifying new suppliers, or renegotiating supply contracts. In short, for the job they are really paid for.
The reason for this situation is simple: while growing through mergers and acquisition, companies amass multiple information systems – so called “legacy systems” – to a complex plethora of sources extremely time consuming to manage and navigate through. “Just imagine – a head of procurement at a pharma company told us recently – to look all day long for purchase orders, contract histories, supplier assessments from the last 2-3 years out of 3-5 different systems (each of our divisions has its own!), then format them, interpret them, and then – finally – think about how to define the strategic line to maintain with the vendor. And this for each and every one of the hundreds of vendors your department is responsible for! No wonder we just focus on the few top vendors and often neglect the others!” Indeed, in such a situation, it is very difficult to fulfil a company´s sourcing mission and being able to consolidate purchase volumes, standardize/reduce number of vendors, sign enterprise-wide agreements, drive global sourcing, and so on.
The good news: technology recently became mature enough to help overcome this situation. In particular Big Data Solutions – i.e. software solutions that are able to meaningfully consolidate and interpret a large amount of structured and unstructured information from multiple sources, such as legacy systems, internet, social media, etc. – have entered the scene: Software such as Google Search Appliance, Expert System, or Lexmark, nowadays have the power to fully automate most of the tedious retrieval, standardization, and consolidation processes so far carried out manually or semi-manually by sourcing professionals, with a reduction of the manual effort from many days down to a matter of seconds. By doing so, they release valuable manpower that can be reallocated on more value-adding activities.
However, these technologies are not just “plug and play”, and require a careful tailoring upon the needs of a company and upon its spend structure. Just consider, how different the process and the related information needs are when buying a direct material that is commoditized – where supply markets dictate the rules and prices are often indexed– compared to when buying some one-time project activities- where reputation of suppliers and unit prices are more relevant. Furthermore, introducing successfully these technologies require a substantial transformation of the way of working at the company, making sure all relevant sourcing professionals embrace and get the most out of them. Neglecting these aspects exposes a company to the risk of having a marvelous tool that does not do what it should.
At execon, we have supported several Big Data transformations in Procurement in pharma and have identified five mantras that are at the root of the successful ones:
Get strong sponsoring from business / function, not from IT. In fact, IT departments tend to have different priorities (such as system consolidation, IT cost of ownership, or technology standards) that may clash at least in the short term with what the business requires. Here it is key that the business or the procurement function takes over the lead and sets the requirements for their process.
Learn from others. Understand how procurement in other industries is extracting value from Big Data. For example, the car manufacturing industry is using Big Data and predictive analysis for early detection of suppliers’ risks by regions and category.
Pilot and rollout approach category by category. Every company is differently organized and purchases different things, so that no single blueprint can be simply rolled-out without adaptions. To that end, and to ensure success, we recommend starting the journey within one or two categories, with strong involvement of the related managers to drive change and only when the template is successful and “bullet-proof” roll it out to other categories.
No standardization at any costs. We often experience clients that want to drive the standardization agenda to the utmost, thereby often missing the benefits of tailored solutions. For example, an IT-mandated “all-Microsoft-strategy” forced a mid-sized pharma to use comparably weak technology, which resulted in end-users boycotting and killing the project
People first! Like every good transformation, it is necessary also in procurement to get to the roots of the “need for change” to ensure at the end to fill the gap and to get the necessary support before and after go-live. A transformation run from a closed-door office is inevitably doomed to fail.
We have also developed a roadmap in 10-steps that systematically addresses all aspects of a Big Data transformation:
1. Engage with business and procurement, and create a transformation story focused on a solution in procurement
2. Identify a category / commodity to start with, and engage with the people managing it
3. Mapping as-is information flow and processes/ identify major gaps to ideal state
4. Define future information flow and processes with special attention to the source / format / ending point of each data set
5. Identify best IT solution that fits into future information flow and processes
6. Discuss with vendors about solution & costing
7. Evaluate ability rollout to other categories
8. Complete IT implementation
9. System integration / user acceptance test
10. Training of all users & go-live
We followed this roadmap recently within the design and roll-out of a Big-Data solution at one of our pharma clients to automate a specific part of the supplier meeting preparation process, where we were eventually able to reduce the processing time of the documentation for vendor meetings from eight working days to 30 minutes per vendor meeting, with a more than 100-fold productivity increase! Concretely, we “automated” the answer to questions like “How much is the purchasing volume in the different business units and business areas?”, “Which suppliers are already registered at group level and what are their suppliers’ evaluations?”, “How is the material price development looking like (material surcharges, cost structures of the raw materials price development) and how does this effect individual products, as well as parts suppliers?”, etc.
This and other examples show that smart leverage of Big Data in procurement can concretely reshape the way sourcing is done, and suppliers and eventually entire supply chains are managed, significantly impacting on their total cost position. However, after many years of “we always did it like this”, many pharma companies still struggle at the thought of changing established practices embrace change and new technologies. Those who will recognize the intrinsic potential of Big Data in procurement will be better placed in an industry that is aggressively looking to keep its cost under control.
Lorenzo Nanetti (lorenzo.nanetti@execon-partners.com) is a partner with execon partners specializing in IT strategy and big data solutions
Lorenzo Formiconi (lorenzo.formiconi@execon-partners.com) is a managing partner with execon partners specializing in procurement strategy & processes

Baar, Switzerland. October 30th, 2015