How a Japanese data analysis platform helps businesses turn scattered records into decisions they can act on today, not next month

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Somewhere in your organization right now, a manager is waiting on a report. Sales figures live in the point-of-sale system, inventory sits in a warehouse database, and last month's promotion numbers are buried in a spreadsheet someone emailed three weeks ago. By the time it's all stitched together by hand, the decision it was meant to inform has already been made — or missed.

Inventory distortion — the combined cost of stockouts and overstocking — is projected to cost the global retail industry roughly $1.7 trillion in 2026, about 6.2% of worldwide retail sales, according to long-running research from IHL Group. Behind that number is a familiar scene: an empty shelf when a customer wants what's on it, or a backroom full of stock nobody needed that much of. Either way, the business finds out too late to do anything about it.

The common thread in almost every one of these losses is the same: the data needed to catch the problem already existed somewhere in the business — it just wasn't anywhere useful, fast enough, to act on. That is the exact problem Dr. Sum was built to solve.

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What Is Dr. Sum, Exactly?

Dr. Sum, developed by Japanese enterprise software company WingArc1st, is a data analysis platform used by more than 7,200 companies worldwide. Instead of stitching together a database, a reporting tool, and an integration layer from three different vendors, Dr. Sum packages all three into a single product:

• A high-speed analytical database engine purpose-built for aggregating large volumes of data

• A flexible user interface — Excel, web browser, tablet, or a connected BI tool — so both analysts and frontline managers can self-serve

• No-code data integration tools that pull information in from ERPs, point-of-sale systems, spreadsheets, and IoT sensors

The point isn't just to store data somewhere central. It's to make querying and consolidating huge, messy, multi-source datasets fast enough that analysis becomes part of daily decision-making, instead of a specialist project that takes a week to turn around.

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The Engine Room: How the High-Speed Aggregation Actually Works

At the center of Dr. Sum is its database engine, and this is where the "high-speed" claim earns its keep. Most transactional databases are row-based — optimized for retrieving single records, like one customer's order. Analytical work does the opposite: it scans millions of rows but touches only a handful of columns at a time, such as total sales by region by month. Dr. Sum's engine uses a patented columnar database architecture that stores and compresses data column-by-column rather than row-by-row, which sharply cuts how much data the engine has to read to answer an aggregation query.

Layer an in-memory processing engine on top of that columnar structure, and the performance becomes dramatic: Dr. Sum is built to aggregate on the order of one billion data records per second. In practice, that means queries that used to run as overnight batch jobs — or that IT quietly rationed because they strained the servers — can instead run on demand, mid-meeting, without complex database tuning.

Because the engine still runs efficiently off disk-based storage (SSD/HDD), companies don't need to over-invest in expensive high-memory hardware just to get this performance — the in-memory engine is available as an extra gear for the heaviest workloads. Dr. Sum also runs Python scripts directly against the data it holds, opening the door to machine learning use cases such as demand forecasting and predictive maintenance, without exporting data to a separate analytics environment.

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From Raw Data to Ready Insight: Integration Without the Headaches

A fast engine is only as useful as the data feeding it, and this is usually where analytics projects stall. Dr. Sum's integration layer is built for the reality of enterprise data — inconsistent, scattered, and not always machine-friendly — without requiring a developer for every new source:

• Excel Extractor converts awkward spreadsheet layouts — merged cells, summary tables, multi-row headers — into structured, database-ready data

• Data Funnel captures and processes IoT and sensor data down to the microsecond, without programming — useful for production lines, cold-chain monitoring, or connected retail equipment

• Dr.Sum Connect is a no-code ETL tool with connectors for common data sources and more than 100 pre-built processing steps, for building repeatable data pipelines

• SecureTransport handles data movement for organizations that need to integrate on-premises systems, whether or not the rest of the stack runs in the cloud

On the output side, teams aren't locked into one interface. Dr.Sum Datalizer for Excel lets analysts who live in spreadsheets drill down, filter, and build calculated fields without leaving Excel. Dr.Sum Datalizer for Web lets an administrator pre-build report templates so frontline staff can self-serve with one click from a browser, and a tablet-optimized view supports store or floor staff on the move. Organizations that want richer visualization can connect Dr. Sum natively to WingArc1st's own MotionBoard dashboard platform, as well as to Microsoft Power BI and Tableau.

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Retail in Focus: Solving the Multi-Store Data Puzzle

Retail is one of the clearest illustrations of why this matters, because the difficulty of retail data isn't really about volume — it's about fragmentation. A single mid-sized chain might run point-of-sale systems in 150 stores, an e-commerce platform, a warehouse management system, and a supplier data feed, each holding one piece of the picture, none of them talking to each other in real time.

Picture a fashion and lifestyle retailer with exactly that footprint: 150 physical stores plus an online store, several thousand active SKUs, and new product lines launching every few weeks. Today, head office pulls together a company-wide sales and inventory picture at month-end — by which point slow-moving stock has already been marked down and fast-moving stock has already sold out in half the stores. Regional managers can see their own numbers reasonably quickly; nobody can see all 150 stores side by side without waiting for IT to run a report.

Here is how introducing Dr. Sum and MotionBoard changes that picture:

• Dr.Sum Connect and SecureTransport pull POS transactions, warehouse stock levels, and e-commerce orders from every source into Dr. Sum on a continuous or nightly schedule, with Excel Extractor handling the merchandising spreadsheets that inevitably still exist

• The columnar, in-memory engine aggregates sales and inventory across all 150 stores and every SKU in seconds, whether the question is "total revenue this morning" or "which stores are a week away from stocking out on this SKU"

• MotionBoard sits on top as the visualization layer, giving head office a live, drillable view of sales and stock by store, region, and product, and giving individual store managers a simpler view scoped to their own location

• Python integration inside Dr. Sum runs demand-forecasting models against the same consolidated sales history, flagging replenishment needs before a shelf actually goes empty rather than after

This combination isn't hypothetical. WingArc1st has reported a comparable real-world deployment: tutuanna, a Japanese wholesaler and retailer of socks and innerwear with roughly 250 company-owned stores (450 including franchises) plus an e-commerce business, implemented Dr. Sum together with MotionBoard to build a store-level data analysis platform. The result was sales and inventory data available in as little as two seconds — in a business where, as WingArc1st notes, product ranges are large and turn over in short cycles, exactly the conditions that make manual consolidation impractical.

For our illustrative 150-store retailer, the payoff would follow the same pattern: fewer stockouts and the customers they cost, less markdown on overstock, and a head office that manages the whole chain by watching a live dashboard instead of waiting for a spreadsheet.

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Why Build This with PT Sazanka Henig Solusi

The same pattern that shows up in retail — data trapped across systems, aggregation too slow for daily use, insight arriving after the decision — shows up in manufacturing, logistics, and finance too. Dr. Sum's architecture doesn't change; only the data sources and the questions being asked do. And Dr. Sum rarely operates alone: pairing its aggregation engine with MotionBoard for visualization is the most common setup, and the same consolidated data can also feed process automation tools like UiPath or Microsoft Power Automate — for example, automatically generating a purchase order the moment Dr. Sum flags a stock shortfall, closing the loop between insight and action.

Implementing a platform like Dr. Sum is straightforward on a spec sheet and considerably harder in practice: mapping the right data sources, designing the aggregation logic, and building dashboards people actually use every day. That is the work we do. PT Sazanka Henig Solusi is an IT consultancy built around a simple idea — Simple, Integrated, Intuitive. Dr. Sum sits alongside MotionBoard, UiPath, and Power Automate in our core lineup, which means we design not just your data aggregation layer, but the visualization and automation on top of it.

• Implementation expertise across the full Dr. Sum and MotionBoard stack, not a generic BI rollout

• Data integration design (ERP, POS, IoT, spreadsheets) built around your existing systems, not the other way around

• A path to pair analytics with automation, so insight from Dr. Sum can trigger action through UiPath or Power Automate

• Hands-on support from scoping through go-live and beyond

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Ready to Turn Your Data Into a Decision Engine?

Every day your data stays scattered across systems is another day your business is deciding on yesterday's information — or last month's. Dr. Sum, paired with the right implementation partner, closes that gap.

Talk to PT Sazanka Henig Solusi about what a Dr. Sum deployment could look like for your business. Please‍ contact our expert:

Hananto Pandu SE., S.Kom., Ak., CA., CPA., ASEAN CPA. - 0896 3626 1684

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Best Regards,

Yohannes Ekaputra Sananto SE. MSc.

yohannes.sananto@sazankahenig.com

Financial Product Consultant

PT Sazanka Henig Solusi

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Sazanka Henig Solusi is a Jakarta-based enterprise technology partner delivering simple, integrated, and intuitive solutions across Enterprise Performance Management, business intelligence, process automation, generative AI, compliance, HR technology, and cybersecurity — helping Indonesian enterprises turn complex business transformation into a lasting competitive advantage.

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