Category Archives: Enterprise Applications

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S&OP is not a Supply Chain Thing

Monday, August 16th, 2010

Though many lump S&OP into “supply chain,” as Tom Wallace reminds us, from 5,000 feet, Executive S&OP is a process that requires ownership not only from supply chain (AKA operations) but also sales, marketing, finance, product management, and above all, senior management. I like to group the S&OP stakeholders into:

Front Office: Sales, Marketing, Product Management
Back Office: Finance and Operations (AKA Supply Chain)

The role of the front office, specifically sales and marketing executives, is to own the revenue and mix forecast of the company. This is “Sales and Marketing Management’s commitment” to the process as Oliver Wight puts it. To be clear, this means operation’s demand planners, typically using supply chain tools, are not the owners (see Demand Planning’s Achilles’ Heal). This complete Sales and Marketing forecast drives the supply planning and at minimum influences, or in fact is the seed for, the finance plan.

S&OP Effectiveness vs. Ease of UseAs highlighted in “S&OP: What’s next after 30 years“, there is a need for easier, more effective S&OP tools for Sales and Marketing to define their commitment to the CEO and on down the food chain. This is key to getting to the next level per AMR’s S&OP maturity model. Among the tools available today for the Front Office, the worst may be ERP. Surprising or not, I have seen sales operations enter long term “forecast” sales orders (on behalf of Sales and Marketing) into ERP systems like SAP and Oracle, that are then exported and rolled-up into Excel to represent an S&OP forecast (at Fortune 100 companies, mind you). With my supply chain background (at i2 and Manugistics, now JDA) I have also seen advanced supply chain demand planning tools rolled out to Sales and Marketing including SAP APO and Oracle Demantra—all in vain—too many times, much like complex financial planning systems like Cognos or Hyperion.  The latest Gartner S&OP Marketscope echos this tool gap.  Excel, as hellish as it can be, surprisingly may be, at least, a better option than the latter ones.

Another tool often experimented with is CRM with its user-friendly and mature  “web 2.0″ technology (i.e. sales force automation like Oracle CRMOD, Microsoft Dynamics or salesforce.com). The world of leads, campaigns and opportunities is indeed the “language” of sales and marketing, but as many learn the hard way, CRM is not the right tool for forecasting mix and for departmental collaboration, despite its demand-related data richness and ease-of-use for sales (see CRM vs forecasting post).

What are we left with for Sales and Marketing? Looking at the quadrant above, is there an S&OP option for Sales and Marketing with Demand Planning and Financial Planning’s forecasting robustness and CRM’s ease of use and forward-looking sales data? In my next blog I will detail how companies like Sharp and Lineage Power have gotten to the next level in S&OP and reaped tremendous benefits. These companies equipped Sales and Marketing to quickly ramp up and own the S&OP forecast for the company as best practices would have it.

Specifically I will dive into how the right front-office solution can transform each step of the Executive S&OP process (per Oliver Wight):

  1. Marketing/Events Activity Review
  2. Demand Review
  3. Supply Review
  4. Demand and Supply Balancing Review and
  5. The Executive Review.

Until then, let me know how you collect Sales and Marketing input for your S&OP process, and how much ownership of the forecast your Sales and Marketing teams claim!

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S&OP: What’s Next After 30 Years?

Wednesday, July 14th, 2010

S&OP BalanceAs its forefathers including Oliver Wight would remind us, S&OP is a very mature process. The objective of S&OP: to align demand and supply in a financially sound manner. Sounds simple, yes? Yet after more than 30 years of practice, most companies still struggle to achieve success with S&OP. AMR Research’s current survey (as presented by Jane Barrett) found that 67% of companies are stuck at Stage Two of what AMR describes are the four stages of S&OP maturity. Let’s look at the state of S&OP practices today and some key implications of recent S&OP and Integrated Business Planning (IBP) research from AMR and Gartner, Inc.

We all know the importance of effective sales and marketing organizations. Especially in a fast-changing economy, sales and marketing effectiveness drives profitability disproportionately. When sales, marketing and channel partners (the “front office”) are effectively engaged with finance, demand planning and supply chain (the “back office”), the company fires on all cylinders. Case in point, Bob Johnson of Gartner Inc. recently presented research demonstrating it was excellence in the front-office side of S&OP that had the greatest impact on allowing many semiconductor companies to stay profitable during the last downturn. The ideal process starts with the front office accurately sizing up the total future demand, or shall we say, revenue potential.  The inputs to S&OP from the front office are bottom-up forecasts of both units (volume) and ASP (price) from sales reps, marketing/product managers and their executives. This rich forecast becomes the baseline for finance, demand planning and supply chain to engage.  Strategic S&OP issues and scenarios can then be escalated to executives for evaluation, while past performance and forward-looking metrics are assessed. The end result? The products customers want are built, and available for delivery, to their delight!

Guess what’s the #1 gap in S&OP today? AMR’s 2010 survey ranked sales and marketing input as the most important aspect of S&OP, yet one of worst performing areas. S&OP leaders assume the demand planning process can adequately incorporate sales and marketing forecasting, including new product forecasts. However, the tools they use to manage the process—demand planning applications—were not built for the sales and marketing people managing sales pipelines, new product launches and marketing campaigns. Even S&OP solutions like Demantra and SAP APO (demand planning applications with S&OP lipstick) lack the basic capabilities needed by sales and marketing—such as an intuitive user-interface and real-time data integration with CRM systems like Oracle CRM On Demand and salesforce.com’s Sales Cloud. It’s no surprise that 51% of companies still use Excel spreadsheets and the like for S&OP (per AMR’s 2010 S&OP survey). But when go-to-market strategies, or detailed sales forecast inputs are incorporated from Excel spreadsheets, accuracy and credibility are lost with operations, and therefore the possibility of reaching reaching a high level of S&OP maturity. Note that on the “OP” side in contrast, supply chain applications (often well-entrenched from over the past decade) can provide a reasonable means to gauge the capability to meet demand (AKA supply planning) and even quickly gauge the impact of S&OP scenarios.

So what lies ahead? S&OP has a bright future. Notably Tim Payne, Research Director, Gartner, Inc., predicts the market for S&OP solutions will grow at around 15% to 20% per year for the next few years1. The challenge for companies wanting to evolve from a reactive S&OP process to one that is collaborating and orchestrating is to get effective S&OP engagement from sales and marketing, including their executives. In my next post, we’ll take a look at how Right90 customers are reaching greater S&OP maturity with a purpose-built forecasting solution for sales and marketing that effectively engages sales and marketing. Even the executives.

1MarketScope for Sales and Operations Planning, 20 October 2009

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Difference #4: Scoring the Sales Forecast to Assess Quality

Monday, July 12th, 2010

Sales Forecast to Assess QualityOnce companies have created their sales forecasts, they often wonder what type of tiger they have by the tail. Which leads us to:

Difference #4: How systems help companies score the sales forecast to assess quality and reliability

The key question every business leader wants answered is:

How good is my sales forecast and how much can I rely on it to predict what I am actually going to sell?

Best-in-class companies have a consistent, systematic way to score and measure ongoing forecast accuracy, bias and completeness. They look at the forecast score by individual forecaster, region, product, and channel.

Scoring the forecast at a granular level enables them to:

  • understand where the likely risk is in the forecast
  • anticipate how good the forecast is going to be
  • give their company confidence in where to act
  • hold individuals accountable to the commits they are making to the company.

Back to our ball game — except now we’re looking at how to keep score.

A Sales Forecasting System has a built-in way to score the forecast and to assess its historical accuracy by slice (customer, product, region, time). A Sales Forecasting System also provides a way for Sales Managers to use the aggregated scores to manage forecast risk. This enables the Sales Managers to develop higher confidence in the forecast and offer better guidance on forecast outcomes to their peers in other functional areas, like operations and finance. Best of all, a Sales Forecasting System provides the tools necessary to hold individuals accountable and reward/penalize good/bad forecasting. By having an objective way to understand the quality of the forecast, companies can hold all parties responsible for improving it. As the old saying goes, “What can’t be measured, can’t be managed.”

A CRM System does not have a native way to score elements of the forecast. If one is desired, it needs to be custom-built, usually in conjunction with a Sales Analytics System. And, per our previous posts, the CRM system can only work with new business opportunity data which is a subset of the complete sales forecast.

A Sales Analytics System can be configured to measure the accuracy of the forecast elements that live within the CRM system, but this usually requires a custom-built set of analytics, in conjunction with customizations to the CRM system.

Once again, combining CRM and Sales Analytics is not enough to fully equip your sales team with the right equipment to win the game. One of the most intriguing books on winning the game with analytics is Moneyball. Companies can play Moneyball with a great sales forecast. In my next blog, we’ll discuss how to use the forecast to drive business processes.

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Difference #2: Collaboration in Building the Forecast

Wednesday, May 19th, 2010

Our second difference between CRM, sales forecasting and sales analytics revolves around how they handle the forecasting business process. Sales forecasting is one of those business processes that requires deep levels of collaboration to drive a good outcome for a company.

Difference #2: How systems support cross department collaboration in building the forecast

Although the sales forecast begins with a bottoms-up commit from sales people, many other departments are involved in constructing and vetting the sales forecast. The input from sales people is the start of a collaborative process that should result in an enterprise demand forecast. This integrated demand forecast reflects inputs and judgments from many people including executives, sales operations, product management, marketing, demand planning and finance.

A Sales Forecasting System understands the part all of these stakeholders play in the sales forecasting process and is configurable enough to support the definition of a business process that allows these individuals to contribute and collaborate in a way that is predetermined by the company:

  • Executives can forecast tops-down
  • sales people can forecast bottoms-up
  • product managers can forecast by product
  • sales-people can forecast by customer
  • product managers can forecast new products
  • finance can forecast cost.

An enterprise sales forecasting system allows the complete process. The entire enterprise demand forecast can be captured along any dimension by all stakeholders. This results in a complete and timely forecast that is actionable by any part of the company.

A CRM System is focused mainly on the sales people and capturing how they think they are doing with regard to new opportunities. Most CRM systems do not anticipate collaboration around the forecast by the other stakeholders. To achieve this, they need to be customized or the process needs to happen outside of the CRM system. In order to generate a complete sales forecast, the new business opportunity forecast contained in CRM is often augmented by spreadsheets that track the run-rate, or recurring business sales forecast. For many companies, new business is a subset of recurring business.

A Sales Analytics System allows other departments to see how the new business pipeline in CRM is evolving but does not otherwise aid cross department collaboration, or in creating a complete forecast collaboratively.

Sales forecasting is an extremely collaborative process that touches both the front office and the back office of every company. Many companies support that process with a hodgepodge of applications and systems, from CRM to Excel to analytics/BI to ERP demand planning. It’s almost as if each function brings their own bat and ball to the party. This makes for a very interesting and chaotic game for most companies.

Next, we’ll look at how companies have brought this game under control.

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Customer Thought Leadership: Sales and Marketing Collaboration

Friday, May 14th, 2010

This is the second installment in our thought leadership series from our Portland roundtable. We will cover three topics:

Sales and marketing collaboration proved to be a lively topic. Not surprisingly, the cats and dogs don’t get along much of the time. However, an actionable sales forecast can foster productive discussions that lead to better collaboration not just between sales and marketing, but between sales and other areas like operations. Our key learnings follow:

Key learning #1: Each area of the company has a different view and something to add to the party.

Our thought leaders had many different processes for getting from sales forecast to fulfillment. One company’s process was that sales generated the forecast, marketing vetted it and gave it to operations who built exactly to their forecast. Another’s was that the factory built to maximize their profit margin and then sent it to sales and marketing to sell, sell, sell, regardless of whether their customers wanted it or not. Either extreme doesn’t do a good job of linking feedback to the forecast. In the former, inventory is not optimized. In the latter example, the company could be doing 10-20% more revenue per year if marketing and sales had the  product they wanted, not just what the factory built. Both of these companies put sales forecasting systems in place to bring the various views together, as the forecast application can capture the different views of sales, marketing and operations into a common system of record, while tracking changes. This lets the organizations focus collaboration on what the data is telling them, not on whether or not the data is good. This is a much more productive discussion for these companies – focus on optimizing the unconstrained customer demand forecast with what the company can deliver.

Key learning #2: Responsibility and compensation drive behavior.

Regardless of the process, compensation drives behavior. When marketing runs the forecast, they can impact sales compensation by constraining product to make their inventory bonus, while sales doesn’t have the right products to sell. When the factory runs the process, their comp is to optimize inventory, not revenue which impacts both marketing and sales compensation. When sales runs the process, they can affect operations compensation (e.g. sales may have visibility to margin, but if they’re not comped on it like operations, they won’t optimize their forecast for margin in addition to revenue). Putting in the right compensation drivers is difficult for most companies. Many focus on one end or the other of the sales forecast to fulfillment process. As one thought leader asked another, “Your marketing forecast affects the sales team’s comp when the units are wrong. How does sales like you then?” The reply? “More when inventory is available.” All of the companies recognized that aligning compensation across all the functions is an area of opportunity to drive better behavior for their company.

Key learning #3: New product introductions are the most fun.

New product introductions (NPI) are the riskiest part of any forecast. Run rate or recurring business is much easier to forecast, and is more predictable.  But creating a forecast for an NPI is a work of art, not science. One thought leader’s company has the product team focus on the idea of what the product will look like in the context of macro level items, like input from big customers, consumer data, and competitive products. Sales, of course, has a different view. Their forecast for NPI starts with sales, then goes to marketing, and then to sourcing. This insures that input from sales on new items is definitely seen by marketing, and seen earlier. It is better to have sales call the baby ugly, and let marketing know. And many times, sales was right.

The best analogy of this session — one of our thought leaders likened a new product introduction to flying an F18 by the wire. For those of us who don’t know, when an F18 takes off from an aircraft carrier the pilot is not actually flying the plane. Pilots make too many changes to the stick and the on-board computers can’t keep up. The computer takes care of the plane’s takeoff, then the pilot takes over once airborne. For a NPI, marketing should launch the product, and then sales can fly it. Of course, operations had to build the plane first!

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