Most Sales Managers in manufacturing and engineering businesses would complain that building sales forecasts with any degree of accuracy takes a lot of time and is a painfully complex task. But if there’s anything that your management and owners love, it’s predictability. And more important, proper sales forecasts are essential to develop manufacturing operational and strategic plans that will help the business to survive in today´s rough economic times.
Our customers from manufacturing and engineering industries specifically mention having problems extracting the following accurate information from their sales process:
- What is the current state of our pipeline? How many leads, opportunities and RFIs (Request for Information)/RFQs (Request for Quotation) do we have out there? Which status do the opportunities and quotes have?
- Which products, parts and processes do these opportunities and budgetary quotes contain?
- To which prices and under which discounts are we selling these? How big is the margin? Hence, which quotes are profitable and why?
- How long are our sales cycles? (And why?)
- What can we expect for the next quarter?
Where is the problem in getting the numbers right?
In manufacturing and engineering companies the sales process is scattered due to the nature of the business. Sending out a quote to a customer in these industries requires collaborative effort between the sales person and engineering, purchasing or other specialized departments. A Bill of Material (BOM) can contain hundreds of items that need to be contributed by specific parties, priced and approved by product specialists and sales managers. This process is often driven by the sales people themselves and requires a lot of data exchange. Today´s options to exchange data are not too bad from a user perspective. Employees use emails, company file sharing servers or file sharing services like Dropbox or SharePoint.
The problem for the reporting manager occurs once he needs this data to be consolidated and analyzed. As by the nature of the sales process, this data is spread in different file formats, different locations and oftentimes not even available. But as soon as all relevant numbers are consolidated a second problem reaches the surface and this concerns the accuracy of this data. And a third would be the time that passes between the initial need of numbers and the effective delivery of the manually collected data.
The answer is transparency.
As you have come to the conclusion that the operating model of your sales process does not deliver the necessary information to analyze, plan and forecast your business, two steps are necessary to overcome this dilemma:
Step 1: You have to gain visibility into accounts, quotes, products, prices and discounts and change the mode of delivery for this data. Instead of collecting this information from various locations and extracting it from different media and formats manually, you need one single source of truth.
Step 2: The collected data needs to be connected, analyzed and displayed in a digestible manner and in real-time. Ideally, the resulting analytics are enriched with insights from previous business data and actionable in order to provide immediate management control capabilities.
Based on real-time revenue estimates further operations can be managed such as timely optimizations of the product portfolio matching the market reactions or competitive situation.
Sounds heavenly? Well, if you want to achieve this level of transparency into your business, you cannot afford to continue collecting data manually but need to automate processes with the help of technology.
Why a standard CRM does not cure your pain
What a relief that all major CRM (Customer Relationship Management) software providers promise to deliver exactly what you are looking for. For example:
- An increase of sales productivity,
- an increase of forecast accuracy,
- and of course the increase of revenue.
The bad news is that standard CRM solutions do not cure the pain of manufacturing and engineering businesses, and here comes why:
As per definition, “CRM systems are designed to compile information on customers across different channels or points of contact between the customer and the company which could include the company's website, telephone, live chat, direct mail, marketing materials and social media.”
For our customers in manufacturing and engineering industries this sounds like a “nice to have” feature set which comes with a heavy investment and does not actually tackle their challenges.
Whilst standard CRMs focus on marketing, lead management and customer behavior on social media, our customers in B2B scenarios struggle to get deep insights into their sales process which centers around the quote or Request for Quotation (RFQ). Multiple price determining conditions as well as the complicated nature of configurable products add up to the complexity of the main objective: to get a realistic view of the pipeline and project a predictable revenue stream.
In order to answer the burning questions that underlie management control and successful business planning, manufacturing and engineering companies rely on forecasting analytics and revenue predictability. Their needs differentiate from those of B2C companies as in the mentioned industries analytics evolve around the focus of the sales process, which is rather the complex product quoting and pricing than the top of the funnel operations of marketing and lead generation.
Matching the general market challenges of shortened product or portfolio lifecycles, the respective market reactions and competitive situations, companies rely on prompt analytics to manage their operations.
Slim margins and a tight economy add to the pressure that forces even small and medium (SME) manufacturing and engineering businesses into automating at least parts of their sales process to keep pace with their competitors. But in order to gain the much needed high level of transparency into the sales process, they will need a solution that is specialized to their industry and delivers real value in terms of in-depth analytics and forecast capabilities.