“Adaptive” Integrated Operations Planning

I ran into an article a few weeks ago proclaiming that IOPS is dead. Another one from HBR attests to the strengths and pitfalls of planning. Vendors from SAP, Oracle, 02Solutions, Anaplan would tell you it has not met its demise. Pundits having suffered through a bad implementation will tell you it is a career death nail. When it comes to S&OP (sales flavor), these projects often suffer from a lack of buy-in from the sales force because it takes so long and by the time the results (target accounts and quotas) are delivered, they are outdated, unrealistic and contradict ingrained sales processes and the character of a sales person.

When you look at the I&OP (supply chain flavor) touted in the late nineties from vendors like i2Technologies, Manugistics, etc., which all got acquired by today’s large ERP vendors, they were black boxes at best requiring a PhD in mathetmatics to reconstruct shipment dates, locations and quantities.

I remember being in a demo at an industrial manufacturer with i2 and once the client asked us to run the algorithm one more time (with a reset), the results came back differently. Nobody could explain it and even our PhD-riddled development team in India took some time to figure this out.

S&OP is hot again but destined to repeat its downfall

This leads me to agree with other followers of this field and conclude that in the ebb and tide existence of SIOP (sales, inventory, ops) we are approaching a tide again. Once it shed its bias towards supply chain management, it became clear that while it still is highly complex; thus, difficult to implement, well governed, departmental solutions may be a good first step in its revival. An enterprise performance management solution, which is (cost)effective is probably just as elusive as the infamous black swan.

If departmental solutions, e.g. for sales planning, are improved in terms of process and underlying data quality and governance, followed by inventory or human resource planning projects, an overarching integrated annual operations plan may actually deliver on its promise.

Most of the existing approaches still only consider people, process and technology but they completely ignore the raw materials….data and the low quality silos they are in.


If you ever wondered about the impact of a lack of (good) planning (courtesy: Bain)


I have seen this repeatedly over the years. Let’s assume goals are agreed upon (stretch #1) and KPIs to measure success are sensible (stretch #2) and key processes are optimized (stretch #3), what do I feed my analytics and predictive tools to plan my staffing plans, my quota plans, my inventory and purchasing algorithms? DATA! However ,that data sits in multiple silos from ERP to CRM, distribution systems, product catalogs, location management systems, HR, Finance, talent management, asset management, work order apps, etc.

They all look at customer, product, location and account hierarchies differently. They all use different reference data like UOM (engl/metric), lat/long (by datum), account codes (DUNS vs database). So how does your average sales operations lead pull together a list of accounts, which should be pursued this year?

A New Way Forward

The classic approach is to merge a past account list with revenue numbers out of the ERP system, merge it with the CRM system of choice (today in the cloud), map it based on DUNS, stack rank it by volume and location, sprinkle some industry CAGR and spend projection from a 3rd party source and assign it to the rep associated with this type of account size (enterprise, SMB) and a territory of the customer HQ. In a more sophisticated version, it will be the location of where decisions for a purchase are made, which makes the DUNS exercise quite obsolete.

The problem with this, you ask? Well, it takes enormous amount of time mapping these sources together and harmonizing hierarchies on top of convincing individual sales leads to give up or own specific accounts, which were artificially diced up by geography. Like wild animals, accounts do not often respect artificial borders.

In addition, this ignores key factors to evaluate before sending the account reps and marketing support staff on this goose chase. Here are more fundamental questions to ask (let’s stick with the technology sector):

  • How long has the customer sponsor been in this account? What about his team? Is it brand new? Was he/she recently promoted?
  • How much experience does he/she have with this type of technology/project/initiative?
  • What about their go-to service provider/vendor? Is there one and how old is this relationship?
  • Is there footprint best-of-breed or one-stop-shop oriented and what is the spend mix between the two? Which vendor owns a commanding percentage of this footprint and is this relationship up for renewal soon?
  • Is the decision process very formalized, IT-run or very decentralized and business focused?
  • Is the customer’s supply and distribution model something we have familiarity with given our staff and prior project experiences?
  • How healthy is this client’s financial position now and what is it projected to be in the near future?
  • Have they been (or will they soon be) audited recently, hit with more regulation or bad press?
  • What does their project prioritization look like?
  • Do they have a history with large scale, transformational projects? How successful is this history?
  • How competitive is the industry the client operates in?
  • What is the average value of a revenue-generating transaction and how many occur in a given year, which can leverage our solution?

Obviously, some of these will have to come from client-rep exchanges but we must assure they get asked at all, asked early, captured and augment an existing view of a client instead of establishing an initial base line.

After you used these to refine your prioritization, which could very well eliminate, add, but at the very least reprioritize accounts in your target account list, you should make this more real-time. After all, this is the age of big data, mobility and real-time access.

So what changes the odds and triggers different reactions if any of these happen after your initial plan?

  • A decision maker changes jobs or he recently brought a whole team onboard?
  • If the customer organization takes on more debt to bridge a revenue shortfall (see oil industry)?
  • Its margins start to suffer due to raw material prices going through the roof?
  • It acquires another company?
  • Its ROCA drops way below industry average?
  • An activist investor starts buying up shares?

Well, these are all “signals”, which could be accessed from public and private data sources, including manual entries by reps in the CRM system, which should affect how you should scale up/down your sales and marketing effort as well as your message to this and similar companies in your list. Tracking these over time allows you to use data to forecast sales linearity and conversion more scientifically, rather than by rule-of-thumb.  In the “olden days” clients used to re-run their supply chain plan every month or week as well to adjust for demand and delivery disruptions.  Advanced firms ran it daily to adjust for demand signals.  B2C companies are becoming masters at detecting and interpreting real-time customer demand signals for sales and inventory management by monitoring Facebook, Twitter, Instagram, etc..  So why do B2B firms not use these sources for sales operations as well?  After all, the volume would be lower.

Not only does it decrease marketing budgets and optimizes sales engagements by asking the tough questions before the reps get their lists, it also generates a more predictable revenue flow by using data for up/downgrading leads as new information becomes available. Use machine learning/AI and give it a second manual glance instead of relying probability changes based on people’s bias.

In the end, this system avoids situations where reps have multiple qualification conversations with prospects, only to find out that while there is interest by one or two lower level staffers, the financial or organizational situation does not allow for a purchase.

Not doing this, enables reps to continue to see the glass as half full (classic sales lense) given the amount of time and heart ache you already invested. When was the last time you have seen a rep walk away from an account? Typically, they throw more resources and ideas at it and see what sticks.

Every email, phone call or visit saved (or invested) decreases (increases) customer acquisition cost (CAC), which hits your income/cash flow statement.

Let’s mull over this one for a while…