I was having discussions a few weeks back with one of our clients regarding actual savings calculation where you calculate how much of the savings you have claimed actually hit the bottom line.
These conversations left some interesting questions: If last year my spend in category X was 100 and now it is 90, what are the main drivers for the change? Did procurement actually contribute to this change?
For direct spend, these guys have a state-of-the art reporting which is used widely in the company, not only by procurement. There is only one truth, one set of numbers which you can find in Sievo. Market-, volume- and currency impact, even substitution impacts, are all isolated from the actual procurement savings reporting. Great stuff!
Now they are interested in expanding the same measurement for indirect spend. To be honest, it is a much tougher journey than for direct spend but still fully doable. Just to keep in mind, there are no short cuts to reach the goal. It’s like crossing a frozen lake in the spring time; it’s tempting to cut corners and just do it, even if there is a risk of falling in the cold water. But it’s better to be patient and find another way to go around the lake, even if it is more time-consuming and requires more efforts.
I have tried to summarize some simple steps, by far nothing revolutionary, to keep in mind on the journey:
- Basic stuff, but if you don’t have dedicated resources, an organization around indirect spend, you will fail miserably. It is wishful thinking that the same resources that manage direct spend could manage indirect spend as well. Indirect spend management requires much more communication with internal stakeholders than direct spend to get commitment and later, results. I wrote an earlier blog post about differences between indirect and direct spend management from procurement point of view. You can find it here.
- When you have the whole organization aligned, create a hierarchy structure that reflects the organization and is supported by the data quality. I have seen structures where companies try to get into very detailed levels but there are really no data points available to support the classification. In these cases, the discussion is dominated by the classification errors and unreliable data. As long as the category managers can do their work effectively, that should be enough. Another bad example regarding category structure is where every node in the category tree does not have an owner/category manager. Why have those nodes if nobody is looking after them? I have had multiple discussions with clients regarding the optimal/best practice hierarchy structure. In my opinion, the key is to find a structure that gives you enough detailed visibility to spend for the category managers to do their work that is still supported by the source data. Four hierarchy levels should do the trick.
- When the organization and hierarchy structure are in place, next question you should focus on is where to spend my money. This is basic spend analysis to understand where the money is going and to find opportunities to focus on.
- Next, you need to track all the initiatives that have been generated by the opportunity identification process. The end result of the process is what we call ‘approved savings’. This is the best guess of the savings that are based on some expected volumes. It is good to involve other internal stakeholders rather than just procurement (e.g. finance) in the process to get credibility behind the numbers. Otherwise, there is a risk of getting into the ‘Mickey Mouse-money’ talks.
- To ensure that the contracts you have negotiated actually have a possibility to hit the bottom line, you need to make sure that contract compliance is monitored and the maverick buying is eliminated to a large extent.
- Finally, you are in a position where you can actually start to see if the savings actually hit the bottom line. Indirect spend is a tricky one to measure, because in many cases, you miss the same kind of data granularity as you might have for direct spend, material codes, quantities etc. But don’t lose faith. There are several ways you can improve the situation:
One way is to implement purchase-to-pay tools to enable easier purchasing activities. The problem with these solutions though is that they are time consuming to rollout, and there is still a great amount of spend (small purchases, consumption based purchases etc.) that never end up in the tool.
A much easier way is to integrate supplier data to your own reporting is what we call data enrichment. For example, logistics is, in many companies, a large, even strategic category, but the visibility to what have been purchased is low (in worst cases, one consolidated invoice row for all the transports during one month). But these suppliers have a good visibility to what they have sold to your company in their systems: routes, volumes etc. Now, when you have consolidated the transports to one or few suppliers in step 4, you have the opportunity to get full visibility to your spend by asking those suppliers to deliver the data to enrich your own invoice data. That way you can split the spend change into different components as described in the beginning of this post.
A third option, if supplier data is not available, you can implement what we call proxies. The idea of proxy is to create a volume component to spend to track that change. One example could be facility management, where a proxy could be floor space, like how much we paid per square for cleaning this year compared to last year.
Before moving into proxies or supplier enriched data, it’s worthwhile to think about what are the more strategic categories and where it make sense to maintain this approach. But for the selected categories, this approach gives you a totally new insight to actual savings and credibility in those savings discussions with other stakeholders.