Scenario:

Our client, who is a fortune 500 company (for 16 years till now) was expecting to induce more value addition in their ordering process, and strengthen its position in the procurement operations. The procurement is initiated via a custom made tool of the client which is linked to the SAP database. We have also a different process mechanism for the each vendor as a result of the contractual arrangement between them and the supply chain management of the client.

Whenever there is any business requirement, the internal customers of the company will be requesting the ordering team to make the procurement necessary. The nature of such transactions can be Capex or Opex, sometimes many such orders could be of short notice (for eg; if the requirement for a consulting work is from 1st of Nov, we might receive the request maybe before few days before the said date). Automated notifications of their requests will be also sent to the internal customers with any change in status of their orders. Also there are some MIS reports which is used by the department to analyse and track the activity of certain business lines they are responsible for.

The Challenge:

We could infer from our analysis that any delay from the ordering team, would have a direct impact in the business’s goodwill, and profitability via delaying the vendor’s pay check. And this occurs by being exposed to a huge risk of losing better payment terms with them (we have our separate payment terms lesser than the market rate with certain vendors) and availing any immediate support in the future that will snowball into a customer dissatisfaction crisis which will have a definite impact in our financials.

In short, our Analysts summarized the client’s total risk (α) in the following formula

∑α= α (market discount from vendors) + α (business from existing customers) + α (goodwill that attains new business)

Also we happily accepted challenge of properly mapping the allotted portion of the ordering process to identify the gaps, and also did an RCA for having a delay accumulated at a particular stage for the orders. From a service delivery perspective our supporting team members have also met the client’s SPoCs to understand their appropriate expectation from us.

Solution:

Our support team closely monitored and studied the process and developed SIPOCs, RCA and ordering matrix report to understand the cause of delays accumulated in the stage of a process.

We then brought a pack of powerful reports (automated, no manual efforts) for internal control, which tracks the orders of the entire department. This clearly helps in understanding ‘who’ is currently working on ‘what’ orders, or if the ordering specialist needs any particular support. The same also assists in identifying how far we have reached in materializing our ordering KPI objectives, how long an item is ‘in issue’, or whether an order is delayed because of any dependency.

Once of the reason why there was a delay in the orders was because of lack of visibility and a deficient control mechanism. Based on our MIS reports we made some corrective actions and created internal policies within the team (Invisor team members) to expedite the ordering process at the same time not at all compromising on the quality of service. We also internally developed efficient ways of identifying errors before hand which minimizes our dependency and subsequently reduces the ordering time.

Result:

The results we achieved through the innovative approaches we induced were outstanding. The following charts elucidate the average time taken from the receipt of a request from an internal customer, till getting the sign off on its PO from the approvers.

The support team Invisor Management Solutions (IMS) were able to generate a PO within an average time frame of 10.34 days, while telecom giant’s average time to generate a PO was 26.88 days. This effectively infers our efficiency to generate a PO 62% faster than the client in similar orders.

IMS had generated a total of 120 PO’s while telecom giant had generated 354 PO’s. Which means our team handled 25% of the total orders of the team.

Therefore we can further understand that 25% of the orders of Vodafone were 62% faster, and the total risk of the telecom giant from the ordering process has decreased by 15.5% from its original position.

Hence we can conclude that telecom giant was able to generate PO’s faster, which improves their relationship with vendors and business reliability to customers.