Naseem A. Malik
Omniva is a privately funded venture fueled by boundless resources and innovation, poised to revolutionize the cloud technology landscape.
Serving as the technology wing of a dynamic portfolio encompassing energy, real estate, and construction, Omniva charts an unprecedented course to claim dominance in compute cloud infrastructure.
The Demand Planner is responsible for researching, calculating, and producing a periodic demand plan that is governed per a Sales & Operations Planning process and serves as an input for the periodic supply plan. The Supply Planner is the Demand Planner’s internal customer. The Demand Planner works closely with sales, product marketing, and finance to trend historical customer consumption behavior of Omniva offerings and modify that trend with non-historical insights from experts in the company and market research. This forward-looking forecast reflects past business reality and future predictions guided by policy, judgment, and forecast accuracy measures.
The role requires the ability to use systems that reflect sales funnel projections, customer orders for Omniva products, and customer use of Omniva products. The demand planner must understand a wide range of market, business, technology, and product terms and their relationships to developing a forecast. 5-10 products may exist per generation with three active generations being analyzed.
The Demand Planner must predict product transitions from generation to generation within accuracy standards. The accuracy of the forecast guides supply quantity, timing, location, and mix products, and thus, has a material impact on the financial performance of the company, ensuring Omniva will neither have insufficient product to sell nor excess inventory.
Since this is a new company, the Demand Planner will help define and test the required features of internally developed software and 3rd party software needed to scale their work.
- Use software products (internally developed or 3rd party) that provide sales funnel prediction details—timing, quantity, location, likelihood, product type, leading indicators of likelihood.
- Use software products that provide customer consumption data—order date, quantity, location, allocation, utilization, trends.
- Use market research products to analyze and predict influences on Omniva customer behavior that will material affect Omniva product forecast.
- Develop or use analytical models to create future (e.g. next 12 months) projections/trends from historical customer behavior such as simple and weighted moving average, simple exponential smoothing, Holt-Winters exponential smoothing, regression analysis, causal regression and time series decomposition. Be able to model slope (growth/decline), seasonality, s-curve, asymptotic, and exponential trends.
- Conduct market research and interview knowledgeable employees to predict size and timing of future (e.g. next 12 months) non-historical influences on the historical-trend forecast. Modify the forecast for likely non-historical events using personal and collective judgment. Examples of non-historical events may be macro-economic changes, armed conflicts, technology shifts or disruptions, substitutes to Omniva products, new competitors to Omniva, large new Omniva customers, Omniva product transitions, new Omniva product categories, new Omniva locations.
- Well ahead of product transitions (e.g. supply lead time plus 1-2 quarters) model current generation to next generation transitions—e.g. ramp down of old product(s), ramp up of new, and cannibalization behavior by new of old. Consider prior similar product transitions and new market research. Gain insights from Omniva experts—e.g. product management, finance, sales, engineering. Propose acceptable bands of uncertainty based on cost and business plans for product availability. Propose actions to react to actual consumption or supply that exceeds bands of uncertainty. Drive consensus and approval in a S&OP meeting. Track actuals to the approved transition plan. Update the model periodically (e.g. monthly) as new information dictates and consensus governs.
- Understand the influence of lead times on forecast from areas such as new product launch, supply of new material for product capacity, on-boarding of new customers.
- Apply basic statistics such as average and standard deviation, assuming normal distribution models, to planning analysis.
- Build models in spreadsheets and operate from spreadsheets for months before more sophisticated tools are developed or purchased. Complete accurate and visually informative forecasts.
- Present visually informative and accurate Demand Plans before a cross-discipline governing body in Sales & Operations Planning (S&OP) Demand Plan meetings. In written and verbal form, communicate in a manner that evokes confidence in the analysis and its outcomes. Lead the conversation towards the most salient points and items in need of discussion/debate. Be consistent from periodic S&OP meeting to meeting (e.g. month to month) to minimized confusion, enhance conversation, and reach consensus more quickly. Formally document meeting results. Track and drive closure to meeting action items.
- Apply correctly and calculate accurately forecast accuracy measures of Attainment and Mean Absolute Percent Error (MAPE). Establish forecast accuracy standards. Report performance of customer consumption relative to forecasts identifying in-range and out-of-range forecast performance. Conduct independent investigation and/or lead a team to investigate forecast error including “5 Why’s?” root cause analysis, ideation (brainstorming and prototyping) of better solutions to address the root cause, and implementation of those solutions, preferably within a planning period (typically monthly).
- Present your analyses before leaders of the company clearly anticipating their preferred level of detail and likely questions.
- Drive features in new more sophisticated software with vendors and/or internal software teams. Document requests and demonstrate prototypes. Test any software for accuracy per the Demand Planner’s own models and work flow.
- Bachelor’s degree in Business, Math, Engineering, Data Science, Finance. MBA is a plus.
- 7+ years experience in demand planning.
- Strong analytical and problem-solving skills.
- Able to calculate average and standard deviation, to derive insights from points in time and trends.
- Proficient in Microsoft Excel including quickly assimilating data from multiple sources, creating pivots, an reducing time from data to information, information to insights, insights to decisions.
- Strong attention to detail and accuracy in work.
- Experience with ERP or supply chain planning software is a plus.
- Excellent written and verbal communication skills, including creation of diagrams, charts, and tables.
- Ability to work independently and manage multiple priorities in a team environment.
This role will be based out of Seattle or Santa Clara, CA.
COMPENSATION & BENEFITS
Competitive compensation and benefits package commensurate with experience.